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1.
MUSCLE Special Session on "
Recognizing humans and human behavior in video", Ovidio
Salvetti, ISTI-CNR, Pisa.
2.
Cultural Heritage,
Vito Cappellini, University of Florence.
3. Image
and Video Quality Evaluation, Alessandro Neri,
University of Roma 3.
4. Color
Image Processing, Eli Saber, Rochester Institute
of Technology, Mark Shaw, Hewlett Packard.
5. Signal
Processing for Ultra Wide Bandwidth, Umberto Mengali,
University of Pisa.
6.
Transceiver Processing for Doubly Selective Channels,
Franz Hlawatsch, Gerald Matz, Vienna University
of Technology.
7. Genomic
signal processing, Alfred Hero, University of
Michigan.
8.
Distributed signal processing in sensor networks, Sergio
Barbarossa, Univ. Roma La Sapienza, Ananthram Swami,
Army Research Laboratory.
9. Bayesian
Methods for Inverse Problems in Image and Signal Processing
Session, N. Galatsanos , University of Ioannina
, Greece.
10.
NEWCOM Special Session
on Advanced Signal Processing Algorithms For Wireless Communications
E. Panayirci, ISIK University Istanbul, H.A. Cirpan, Istanbul
University
11.
Cross-layer Optimization form Wireless Communication Systems
Session, Holger Boche, Technical University of
Berlin, Germany.
12. MIMO
Channel Modelling, Emulation and Sounding, Peter Grant,
University of Edinburgh, Scotland.
13.
Multi-user MIMO communications, Cristoph F.Mecklenbraukerftw.
Forschungs zentrum Telekommunikation, Wien, Austria.
14. MIMO
Transmission Techniques, Wolfgang Utschick, Munich
Univ. of Technology, Germany.
15. MIMO
Testbeds and Rapid Prototyping and Implementation Steps of
MIMO Systems, Markus Rupp, Institute for Communications
and RF Engineering,University of Technology, Vienna, Austria,
Steffen Paul, Infineon Technologies, Munich, Germany.
16. Advances
in Monte Carlo methods for target tracking, Petar
Djuric, Monica Bugallo, Stony Brook University, NY, USA.
17. Signal
Processing in Radar Imaging, Victor C. Chen,
Radar Division, US Naval Research Laboratory, USA, Marco
Martorella, Dept. of Ingegneria dell'Informazione, University
of Pisa, Italy.
18.
Undetermined Sparse Audio Source Separation, Shoji
Makino, Shoko Araki, NTT Communciation Science
Laboratories, Kyoto, Japan.
19. HW
and SW architectures for multimedia streaming systems,
Luca Fanucci, Dept. of Ingegneria dell'Informazione,
University of Pisa, Italy, Fabrizio Rovati, ST Microelectronics,
Agrate Brianza (MI), Italy.
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1-I°) Special session MUSCLE - Recognizing
humans and human behavior in video - 5 papers
Adua 2Ovidio Salvetti (ISTI-CNR,
Italy)
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Automatic Fire Detection in Video
Sequences
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Turgay Celik
(Eastern Mediterranean University, Turkey)
In this
paper, we propose a real-time fire-detector which combines
foreground information with statistical color information to
detect fires. The foreground information which is obtained using
adaptive background information is verified by the statistical
color information which is extracted using hand labeled fire
pixels to determine whether the detected foreground object is a
candidate for fire or not. The output of the both stages is
analyzed in consecutive frames which is the verification process
of fire that uses the fact that fire never stays stable in
visual appearance. The frame processing rate of the detector is
about 30 fps with image size of 176x144 which enables the
proposed detector to be applied for real-time applications.
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Adding geometrical terms to shadow
detection process
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László
Havasi (Peter Pazmany Catholic University, Hungary)
The
elimination of strong shadow in outdoor scenes contain-ing human
activity is addressed in the paper. The main con-tribution of
the introduced method is the integration of geo-metrical
information into the shadow detection process. This novel
approach takes into account the collinearity of shadow and light
direction and completed with a simple colour based pre-filtering.
The final classification step is carried out via a Bayesian
iteration scheme which is general enough to handle further
characteristics of the problem: weak shadow and reflection.
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Human Model and Motion Based 3D Action
Recognition in Multiple View Scenarios
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Cristian Canton (Universitat
Politecnica de Catalunya, Spain); Josep Casas (UPC - Technical
University of Catalonia, Spain); Montse Pardas (Technical
University of Catalonia, Spain)
This paper
presents a novel view-independent approach to the recognition of
human gestures of several people in low resolution sequences
from multiple calibrated cameras. In contraposition with other
multi-ocular gesture recognition systems based on generating a
classification on a fusion of features coming from different
views, our system performs a data fusion (3D representation of
the scene) and then a feature extraction and classification.
Motion descriptors introduced by Bobick et al. for 2D data are
extended to 3D and a set of features based on 3D invariant
statistical moments are computed. A simple ellipsoid body model
is fit to incoming 3D data to capture in which body part the
gesture occurs thus increasing the recognition ratio of the
overall system and generating a more informative classification
output. Finally, a Bayesian classifier is employed to perform
recognition over a small set of actions. Results are provided
showing the effectiveness of the proposed algorithm in a
SmartRoom scenario.
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Visual speech detection using mouth
region intensities
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Spyridon
Siatras (Aristotle University of Thessaloniki, Greece); Nikos
Nikolaidis (Aristotle University of Thessaloniki, Greece); Ioannis
Pitas (ARISTOTLE UNIVERSITY OF THESSALONIKI, Greece)
In recent
research efforts, the integration of visual cues into speech
analysis systems has been proposed with favorable response. This
paper introduces a novel approach for lip activity and visual
speech detection. We argue that the large deviation and
increased values of the number of pixels with low intensities
that the mouth region of a speaking person demonstrates can be
used as visual cues for detecting speech. We describe a
statistical algorithm, based on detection theory, for the
efficient characterization of speaking and silent intervals in
video sequences. The proposed system has been tested into a
number of video sequences with encouraging experimental results.
Potential applications of the proposed system include speech
intent detection, speaker determination and semantic video
annotation.
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Cooperative Background Modelling using
Multiple Cameras Towards Human Detection in Smart-Rooms
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Jose-Luis
Landabaso (Technical University of Catalunya, Spain); Montse
Pardas (Technical University of Catalonia, Spain)
Shape-from-Silhouette (SfS) is the common approach taken to
reconstruct the Visual Hull which is later used in 3D-trackers
and body fitting techniques. The Visual Hull is defined as the
intersection of the visual cones formed by the back-projection
of several 2D binary silhouettes into the 3D space. Silhouettes
are usually extracted using a foreground classification process,
which is performed independently in each camera view. In this
paper we present a novel approach in which 2D-foreground
classification is achieved in 3D accordance in a Bayesian
framework. In our approach, instead of classifying images and
reconstructing later, we simultaneously reconstruct and classify
in the 3D space.
1-II°) Special session MUSCLE -
Recognizing humans and human behavior in video - 4 papers
Adua 2Ovidio Salvetti (ISTI-CNR,
Italy)
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Active Video-Surveillance Based on Stereo
and Infrared Imaging
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Gabriele
Pieri (CNR, Inst. of Information Science and Technologies, Italy);
Ovidio Salvetti (ISTI-CNR, Italy)
Video-surveillance is a very actual and critical issue at the
present time. Within this topic we address the problem of
firstly identifying moving people in a scene through motion
detection techniques, and subsequently categorising them in
order to identify humans for tracking their movements. The use
of stereo cameras, coupled with infrared vision, allows to apply
this technique to images acquired through different and variable
condition, and allows an a priori filtering based on the
characteristics of such images to give evidence to objects
emitting an higher radiance (i.e. higher temperature).
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Contour Based Smoke Detection in Video
Using Wavelets
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Behcet
Toreyin (Bilkent University, Turkey); Yigithan Dedeoglu (Bilkent
University, Turkey); A. Enis Cetin (Bilkent University, Turkey)
This paper
proposes a novel method to detect smoke in video. It is assumed
the camera monitoring the scene is stationary. The smoke is
semi-transparent at the early stages of a fire. Therefore edges
present in image frames start loosing their sharpness and this
leads to a decrease in the high frequency content of the image.
The background of the scene is estimated and decrease of high
frequency energy of the scene is monitored using the spatial
wavelet transforms of the current and the background images.
Edges of the scene produce local extrema in the wavelet domain
and a decrease in the energy content of these edges is an
important indicator of smoke in the viewing range of the camera.
Moreover, scene becomes grayish when there is smoke and this
leads to a decrease in chrominance values of pixels. Periodic
behavior in smoke boundaries is also analyzed using a Hidden
Markov model (HMM) mimicking the temporal behavior of the smoke.
In addition, boundary of smoke regions are represented in
wavelet domain and high frequency nature of the boundaries of
smoke regions is also used as a clue to model the smoke flicker.
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Human Face Detection in Video Using Edge
Projections
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Mehmet
Turkan (Bilkent University, Turkey); Ibrahim Onaran (Bilkent
University, Turkey); Enis Çetin (Bilkent University, Turkey)
In this
paper, a human face detection method in images and video is
presented. After determining possible face candidate regions
using color information, each region is filtered by a high-pass
filter of a wavelet transform. In this way, edges of the region
are highlighted, and a caricature-like representation of
candidate regions is obtained. Horizontal, vertical and
filter-like projections of the region are used as feature
signals in dynamic programming (DP) and support vector machine (SVM)
based classifiers. It turns out that SVM based classifier
provides better detection rates compared to DP in our simulation
studies.
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Multimodal Fusion by Adaptive
Compensation for Feature Uncertainty with Application to
Audiovisual Speech Recognition
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Athanassios
Katsamanis (National Technical University of Athens, Greece);
George Papandreou (National Technical University Athens, Greece);
Vassilis Pitsikalis (National Technical University of Athens,
Greece); Petros Maragos (National Technical University of Athens,
Greece)
In pattern
recognition one usually relies on measuring a set of informative
features to perform tasks such as regression or classification.
While the accuracy of feature measurements heavily depends on
changing environmental conditions, studying the consequences of
this fact has received relatively little attention to date. In
this work we explicitly take into account uncertainty in feature
measurements and we show in a rigorous probabilistic framework
how the models used for classification should be adjusted to
compensate for this effect. Our approach proves to be
particularly fruitful in multimodal fusion scenarios, such as
audio-visual speech recognition, where multiple streams of
complementary features are integrated. For such applications,
provided that an estimate of the measurement noise uncertainty
for each feature stream is available, we show that the proposed
framework leads to highly adaptive multimodal fusion rules which
are widely applicable and easy to implement. We further show
that previous multimodal fusion methods relying on stream
weights fall under our scheme under certain assumptions; this
provides novel insights into their applicability for various
tasks and suggests new practical ways for estimating the stream
weights adaptively. Preliminary experimental results in
audio-visual speech recognition demonstrate the potential of our
approach.
2) Cultural Heritage - 7 papers
Chairs: Vito
Cappellini, Alessandro Piva
AuditoriumVito
Cappellini (University of Florence, Italy)
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Opportunities and issues of Image
Processing for Cultural Heritage Applications
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Alessandro
Piva (University of Florence, Italy); Vito Cappellini (University
of Florence, Italy)
The
application of image processing techniques for the analysis, the
diagnostic and the restoration of artworks remains a very
uncommon practise. Recently, however, there has been a greater
interest on acquiring and processing image data of artworks: the
efforts in this application field have been characterized by
promising results, which proved the advantages that the use of
digital image processing may have on several issues. In this
paper the peculiarities and the state of the ar of this
application field will be described.
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Using Spanning Trees for Reduced
Complexity Image Mosaicing
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Nikos
Nikolaidis (Aristotle University of Thessaloniki, Greece); Ioannis
Pitas (ARISTOTLE UNIVERSITY OF THESSALONIKI, Greece)
Image
mosaicing, i.e., reconstruction of an image from a set of
overlapping sub-images, has numerous applications that include
high resolution image acquisition of works of art. Unfortunately,
optimal mosaicing has very large computational complexity that
soon becomes prohibitive as the number of sub-images increases.
In this paper, two methods which achieve significant
computational savings by applying mosaicing in pairs of two
sub-images at a time, without significant reconstruction losses,
are proposed. Simulations are used to verify the computational
efficiency and good performance in terms of matching error of
the proposed techniques.
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Automated Investigation of Archeological
Vessels
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Martin
Kampel (Vienna University of Technology, Austria); Hubert Mara
(Vienna University of Technology, Austria); Robert Sablatnig
(Vienna University of Technology, Austria)
Motivated
by the requirements of the present archaeology, we are
developing an automated system for archaeological classification
and reconstruction of ceramics. This paper shows a method to
answer archaeological questions about the manufacturing process
of ancient ceramics, which is important to determine the
technological advancement of ancient culture. The method is
based on the estimation of the pro- file lines of ceramic
fragments, which can also be applied to complete vessels. With
the enhancements shown in this paper, archaeologists get a tool
to determine ancient manufacturing techniques.
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Damages of Digitized Historical Images as
Objects for Content Based Applications
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Edoardo
Ardizzone (Universitŕ degli Studi di Palermo, Italy); Haris Dindo
(Universitŕ degli Studi di Palermo, Italy); Umberto Maniscalco
(Istituto per le Applicazioni del Calcolo (I.A.C.) M. Picone -
Italian National Research Council (C.N, Italy); Giuseppe Mazzola
(Universitŕ degli Studi di Palermo, Italy)
This work
presents the preliminary results achieved within a FIRB project
aimed to develop innovative support tools for automatic or
semi-automatic restoration of damaged digital images concerning
archaeological and monumental inheritance of Mediterranean coast.
In particular, this paper is focused on a methodology for
describing image degradation and its meta-representation for
content based storing and retrieval. Our innovative idea is to
decompose and store in a conventional RDBMS the images content,
considering the damages as objects of the images. Moreover, a
set of descriptors(a subset of MPEG7 descriptors) is used for
the damage meta representation aimed to content based
application. Finally we developed a user-friendly database
management tool for manipulating the contents of the database
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The image processing system for art
specimens: Nephele
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Miroslav
Benes (Institute of Information Theory and Automation, Czech
Republic); Barbara Zitova (Institute of Information Theory and
Automation, Czech Republic); Jan Flusser (Institute of Information
Theory and Automation, Czech Republic); Janka Hradilova (Academic
Laboratory of Materials Research of Paintings, Czech Republic);
David Hradil (Academic Laboratory of Materials Research of
Paintings, Czech Republic)
In our
paper we introduce comprehensive solution for processing and
archiving information about artwork specimens used in the course
of art restoration - Nephele. The information processing based
on image data is used in the procedure of identification of
pigment and binder present in the artwork, which is very
important issue for restorers. Proposed approach geometrically
aligns images of microscopic cross-sections of artwork color
layers - image registration method based on mutual information,
and then creates preliminary color layer segmentation - modified
k-means clustering. The archiving part of the Nephele enables
creating database entries for painting materials research
database, their storage, and creating text-based queries. In
addition to these traditional database functions, advanced
report retrieval is supported; based on the similarity of image
data, comparing either the ultraviolet and visual spectra images
(using co-occurence matrices and color similarity functions), or
the energy dispersive X-ray images (using features computed from
the wavelet decomposition of the data).
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Multispectral UV Fluorescence Analysis of
Painted Surfaces
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Anna
Pelagotti (INOA, Italy); Luca Pezzati (INOA, Italy); Alessandro
Piva (University of Florence, Italy); Andrea Del Mastio
(University of Florence - Media Integration and Communication
Center, Italy)
A novel
system has been developed to acquire digital multispectral
ultraviolet (UV) induced visible fluorescence images of
paintings. We present here the image processing needed to
understand and further process the acquired multispectral UV
fluorescence images.
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Analysis of Multispectral Images of
Paintings
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Philippe
Colantoni (Jean Monnet University, France); Ruven Pillay (C2RMF,
France); Christian Lahanier (C2RMF, France); Denis Pitzalis
(C2RMF, France)
One
hundred paintings conserved in several museums have been scanned
by the C2RMF using the multi-spectral CRISATEL camera. These
high resolution images allow us to not only generate an accurate
colour image under any chosen illuminant, but also allow us to
reconstruct the reflectance spectra at each pixel. Such images
can be used for a visual qualitative as well as
measurement-based quantitative scientific analysis of the work
of art. Several image processing tools have been developped to
allow us to perform these analyses. The IIPImage system enables
us to visualize high resolution multi-spectral 16 bit images,
view image details in colour or for each spectral channel and to
super-impose and compare different wavelengths. A complementary
viewing system uses an innovative 3D graphics
hardware-accelerated viewer to allow us to reconstruct the
resulting colour dynamically while interactively changing the
light spectrum. The system also allows us to perform
segmentation, view the colour distribution for a particular
colour-space and perform dynamic spectral reconstruction.
3) Image and Video Quality Evaluation - 7
papers
Adua 3Alessandro Neri
(Universitŕ degli Studi "Roma TRE", Italy)
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H.264 Coding Artifacts And Their Relation
To Perceived Annoyance
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Tobias Wolff
(Darmstadt University of Technology, Germany); Hsin-Han Ho
(University of California Santa Barbara, USA); John Foley
(University of California Santa Barbara, USA); Sanjit K. Mitra (UCSB,
USA)
In this
study we investigate coding artifacts in H.264 baseline profile.
A psychophysical experiment was conducted that collected data
about the subjectively perceived annoyance of short video
sequences as well as the perceived strength of three coding
artifacts. The data provided by 52 subjects is analyzed with
respect to bitrate and intra period of the encoded sequences. A
new data analysis method is presented which is based on a
granular data representation and enables the detection of
multidimensional functional dependencies in data sets. This
method is employed to establish a model for the perceived
annoyance as a function of artifact strength.
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Task impact on the visual attention in
subjective image quality assessment
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Alexandre
Ninassi (University of Nantes, France); Olivier Le Meur (Thomson
R&D, France); Patrick Le Callet (University of Nantes, France);
Dominique Barba (Institut de Recherche en Communications et
Cybernétique de Nantes, France); Arnaud Tirel (University of
Nantes, France)
Visual
attention is a main feature of the human visual system
components. Knowing and using the mechanisms of the visual
attention could help improving image quality assessment. But,
which kind of saliency should be taken into account? A free-task
visual selective attention or a quality oriented visual
selective attention. We recorded and evaluated the discrepancy
between these two types of visual attention. The results will be
given to show the impact of the viewing task on visual strategy.
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No-Reference perceptual quality
assessment of colour image
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Benjamin
Bringier (SIC, Université de Poitiers, France); Noël RICHARD (Université
de Poitiers, France); Chaker Larabi (SIC, Université de Poitiers,
France); Christine Fernandez-Maloigne (SIC, Université de
Poitriers, France)
Image
quality assessment plays an important role in various image
processing applications. In recent years, some objective image
quality metrics correlated with perceived quality measurement
have been developed. Two categories of metrics can be
distinguished: with full-reference and noreference.
Full-reference looks at decrease in image quality from some
reference of ideal. No-reference approach attempts to model the
judgment of image quality without the reference. Unfortunately,
the universal image quality model is not on the horizon and
empirical models establishes on psychophysical experimentation
are generally used. In this paper, we present a new algorithm
for quality assessment of colour reproduction based on human
visual system modeling. A local contrast definition is used to
assign quality scores. Finally, a good correlation is obtained
between human evaluations and our method.
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Estimation of accesible quality in noisy
image compression
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Nikolay
Ponomarenko (National Aerospace University, Kharkov, Ukraine);
Mikhail Zriakhov (National Aerospace University, Ukraine);
Vladimir Lukin (National Aerospace University, Kharkov, Ukraine);
Jaakko Astola (Tampere University of Technology, Finland); Karen
Egiazarian (Tampere University of Technology, Finland)
A task of
lossy compression of noisy images providing ac-cessible quality
is considered. By accessible quality we mean minimal distortions
of a compressed image with re-spect to the corresponding
noise-free image that are ob-served for the case of optimal
operation point (OOP). The ways of reaching OOP for noisy images
are discussed. It is shown that this can be done in automatic
mode with appro-priate accuracy. Investigations are performed
for efficient DCT-based AGU coder for a set of test images. We
also demonstrate that the proposed approach can be applied to
automatic selection of compression ratio for lossy compres-sion
of noise-free images.
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No reference quality assessment of
Internet multimedia services
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Alessandro
Neri (University of ROMA TRE, Italy); Marco Carli (University of
Roma TRE, Italy); Marco Montenovo (HP C&I, Italy); Alessandro
Perrot (HP C&I, Italy); Francesco Comi (University of Roma TRE,
Italy)
In this
paper an objective No Reference metric for assessing the quality
degradations introduced by transmission over a heterogeneous IP
network is presented. The proposed ap-proach is based on the
analysis of the interframe correlation measured at the output of
the rendering application. It does not require information about
the kind of errors, delays and latencies that affected the link
and countermeasures intro-duced by decoders in order to face the
potential quality loss. Experimental results show the
effectiveness of the proposed algorithm in approximating the
assessments obtained with full reference metrics.
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Intelligent Sharpness Enhancement for
Video Post-Processing
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Jorge
Caviedes (Intel Corporation, USA)
Sharpness
enhancement is one of the post-processing stages in the consumer
electronics video chain that operates in an open-loop mode.
Although adaptive behavior is possible, in general there is no
feedback system aimed at maximizing perceived quality. In this
paper we introduce a control system and metric for sharpness
enhancement algorithms. We also discuss the options of
implementing an internal or local control loop, i.e., to control
the basic sharpness enhancement engine at the pixel or region
level, and an external or global control loop for sharpness
enhancement module.
4) Color Image Processing - 4 papers
Chairs:
Eli Saber, Mark Shaw
Adua 2Eli Saber (Rochester
Institute of Technology, USA)
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A Kernel Approach to Gamut Boundary
Computation
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Joachim
Giesen (Swiss Federal Institute of Technology in Zurich,
Canada); Eva Schuberth (Swiss
Federal Institute of Technology in Zurich, Switzerland); Klaus
Simon (EMPA, Algeria); Peter Zolliker (EMPA, Switzerland)
We
present a kernel based method to associate an image gamut
given as a point cloud in three-dimensional Euclidean space
with a continuous shape. The shape we compute is implicitly
given as the zero-set of a smooth function that we compute
from the point cloud using an efficient optimization method.
The feasibility of our approach is demonstrated on a couple
of examples.
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Thin-plate splines for printer data
interpolation
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Gaurav
Sharma (University of Rochester, USA); Mark Shaw (Hewlett
Packard Company, Boise, USA)
Thin-plate spline models have been used extensively for
data-interpolation in several problem domains. In this paper,
we present a tutorial overview of their theory and highlight
their advantages and disadvantages, pointing out specific
characteristics relevant in printer data interpolation
applications. We evaluate the accuracy of thin-plate splines
for printer data interpolation and discuss how available
knowledge of printers physical characteristics may be
beneficially exploited to improve performance.
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HDR CFA Image Rendering
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David
Alleysson (University Pierre Mendes-France, France); Sabine
Susstrunk (EPFL, Switzerland); Laurence Meylan (EPFL,
Switzerland)
We
propose a method for high dynamic range (HDR) mapping that
is directly applied on the color filter array (CFA) image
instead of the already demosaiced image. This rendering is
closer to retinal processing where an image is acquired by a
mosaic of cones and where adaptive non- linear functions
apply before interpolation. Thus, in our framework,
demosaicing is the final step of the rendering. Our method,
inspired by retinal sampling and adaptive processing is very
simple, fast because only one third of operations are needed,
and gives good result as shown by experiments.
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Recent advances in acquisition and
reproduction of multispectral images
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Jon
Hardeberg (Gjřvik University College, Norway)
Conventional color imaging science and technology is ba\-sed
on the paradigm that three variables are sufficient to
characterize a color. Color television uses three color
channels, and silver-halide color photography uses three
photo-sensitive layers. However, in particular due to
metamerism, three color channels are often insufficient for
high quality imaging e.g. for museum applications. In recent
years, a significant amount of color imaging research has
been devoted to introducing imaging technologies with more
than three channels - a research field known as
multispectral color imaging. This paper gives an overview of
this field and presents some recent advances concerning
acquisition and reproduction of multispectral images.
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5-I°) Digital Signal Processing for UWB
Applications - 5 papers
AuditoriumUmberto
Mengali (University of Pisa, Italy)
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Reduced-complexity Multiple Symbol
Differential Detection for UWB Communications
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Vincenzo
Lottici (University of Pisa, Italy); Zhi Tian (Michigan
Technological University, USA)
In
ultra-wideband (UWB) communications, the typical signal
propagation through dense multipath fading offers potentially
very large multipath diversity, but at the same time complicates
receiver design as far as channel estimation and multipath
energy capture are concerned. To strike a desired balance, we
propose a multi-symbol differential detection framework that
bypasses training or costly channel estimation by the use of
autocorrelation principle. Furthermore, resorting properly to
the Viterbi algorithm enables to attain an efficient performance
versus affordable complexity tradeoff solution. Simulation
results demonstrate that the proposed detection scheme is
remarkably robust with respect to the effects of both noise and
multiple access interference.
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UWB Receiver Design for low Resolution
Quantization
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Stefan Franz
(University of Southern California, USA); Urbashi Mitra
(University of Southern California, USA)
Digital
implementation of ultra-wideband receivers requires
analog-to-digital conversion (ADC) at an extremely high speed,
thereby limiting the available bit resolution. Herein, a new
family of receiver structures optimized and tailored to
quantized observations is presented. The generalized-likelihood
ratio test (GLRT) based on the quantized samples is derived and
shown to provide performance improvements in comparison to the
infinite resolution GLRT rule employed on the quantized received
signal. Furthermore, simulation results reveal that four bits of
resolution are sufficient to closely approach the performance of
a full resolution receiver.
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Narrowband Interference Suppression in
Transmitted Reference UWB Receivers Using Sub-Band Notch Filters
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Marco
Pausini (Delft University of Technology, The Netherlands); Gerard
Janssen (Delft University of Technology, The Netherlands)
The
Transmitted-Reference (TR) signaling scheme in conjunction with
the Auto-correlation Receivers (AcR) has gained popularity in
the last few years as low-complexity system architecture for
Ultra Wide Band (UWB) communications. Since the signal template
is directly obtained from the received signal, not only the
noise but also the interference caused by a narrowband (NB)
system operating in the same bandwidth corrupt both the data and
the reference pulses. In this paper we study the effects of a
single-tone interferer on the performance of a TR systems,
measured in terms of probability of error. We also propose a
simple but effective way to counteract the NB interference,
consisting of a bank of notch filters, suppressing the sub-band
containing the NB signal.
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Narrowband interference mitigation for a
transmitted reference ultra-wideband receiver
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Quang Hieu
Dang (Delft University of Technology, The Netherlands); Alle Jan
van der Veen (Delft University, The Netherlands)
Narrowband
inteference (NBI) is of specific concern in transmitted
reference ultrawide band (TR-UWB) communication systems. We
consider NBI in high data rate applications where significant
interframe interference is present due to a very short frame
rate. Oversampling of the correlator output with respect to the
frame rate is used to gather more information for the receiver.
We formulate an approximate data model that includes the NBI
terms, subsequently a receiver algorithm is derived.
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Finger Selection for UWB Rake Receivers
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Sinan Gezici
(Princeton University, USA); Mung Chiang (Princeton University,
USA); Hisashi Kobayashi (Princeton University, USA); H. Vincent
Poor (Princeton University, USA)
The
problem of choosing the multipath components to be employed at a
selective Rake receiver, the finger selection problem, is
considered for an impulse radio ultra-wideband system. First,
the finger selection problem for MRC-Rake receivers is
considered and the suboptimality of the conventional scheme is
shown by formulating the optimal solution according to the SINR
maximization criterion. Due to the complexity of the solution, a
convex formulation is obtained by means of integer relaxation
techniques. Then, the finger selection for MMSE-Rake receivers
is studied and optimal and suboptimal schemes are presented.
Finally, a genetic algorithm based solution is proposed for the
finger selection problem, which works for various multipath
combining schemes. Simulation studies are presented to compare
the performance of different algorithms. Index Terms
Ultra-wideband (UWB), impulse radio (IR), Rake receiver, convex
optimization, integer programming, genetic algorithm (GA).
5-II°) Digital Signal Processing for UWB
Applications - 3 papers
AuditoriumUmberto
Mengali (University of Pisa, Italy)
-
How to Efficiently Detect Different
Data-Rate Communications in Multiuser Short-Range Impulse Radio
UWB Systems
-
Simone
Morosi (University of Firenze, Italy, Italy); Tiziano Bianchi
(University of Florence, Italy)
Low and
high data-rate applications can be foreseen for future
ultra-wideband systems which are based on impulse radio and
proper detection schemes have to be designed for the most
general scenarios. In this paper an innovative frequency domain
detection strategy is tested in two different indoor short-range
communication scenarios where several mobile terminals transmit
low or high data-rate flows to a base station. Both Zero Forcing
(ZF) and Minimum Mean Square Error (MMSE) criteria have been
investigated and compared with the classical RAKE. The results
show that the proposed approach is well suited for the
considered scenarios.
-
-
Reduced Memory Modeling and Equalization
of Second order FIR Volterra Channels in Non-coherent UWB Systems
-
Jac Romme (IMST,
Germany); Klaus Witrisal (Graz University of Technology, Austria)
This paper
investigates a combination of two approaches to obtain
high-data-rate UWB communication over multipath radio channels,
using low complexity, non-coherent receivers. The first approach
targets to equalize the occurring \emph{non-linear} ISI using
trellis-based equalization, while the second approach aims to
reduce or even avoid ISI by dividing the spectral resources into
(a few) sub-bands. Combination of both concepts allows for a
complexity trade-off between equalizer and RF front-end. Firstly,
a reduced-memory data model will be introduced for the
non-linear sub-band channels, optimal in the sense of the MMSE
criterion. This model is used to study the relationship between
equalizer complexity and performance. The second part of the
paper investigates the performance of the complete system,
before and after forward error control. The system uses QPSK-TR
signaling, but the key concepts are applicable to other
non-coherent UWB systems as well.
-
-
Multi-Target Estimation of Heart and
Respiration Rates Using Ultra Wideband Sensors
-
Natalia
Rivera (Virginia Tech - Wake Forest University, USA)
Vital-signs monitoring devices continue to utilize invasive
sensing methodologies, ranging from skin surface contact
techniques such as the use of electrodes for measuring cardiac
signals (ECG test), to more intrusive techniques such as the
utilization of a facial mask for measuring gas exchange during
respiration. In this paper, we present a wireless radar
technique based on ultra-wideband (UWB) technology for
non-invasive monitoring of heart and respiration rates. Our
technique is based on the detection of chest-cavity motion
through the measurement of UWB signal displacements due to this
motion. We show that the technique provides accurate results
even in the presence of multiple subjects. Specifically, we
investigate the two techniques for estimating breathing and
heart rates in the presence of multiple subjects: (1) the use of
clustering algorithms to isolate the combined position and
breathing/heart rate of multiple subjects and (2) the use of
MUSIC to accurately estimate only the rates. Results are based
on measurements from experiments with multiple subjects in a
laboratory setting.
-
-
Analysis of Threshold-Based TOA
Estimators in UWB Channels
-
Davide
Dardari (University of Bologna, Italy); Chia-Chin Chong (NTT
DoCoMo USA Labs, USA); Moe Win (Massachusetts Institute of
Technology, USA)
In this
paper we analyze and compare the performance of matched filter (MF)
and energy detector (ED) time-of-arrival estimators based on
thresholding in ultra-wide bandwidth (UWB) dense multipath
channels. Closed-form expressions for the estimator bias and
mean square error (MSE) are derived as a function of
signal-to-noise ratio using a unified methodology. A comparison
with results based on Monte Carlo simulation confirms the
validity of our analytical approach. In addition, results based
on experimental measurements in an indoor residential
environment are presented as well. Our analysis enables us to
determine the threshold value that minimizes the MSE, critical
parameter for optimal estimator design. It is shown that the
estimation accuracy mainly depends on large estimation errors
due to peak ambiguities caused by multipath at the output of the
MF or ED and on the fading statistics of the first path. The
evaluation of the performance loss faced by ED estimators with
respect to those based on MF is also carried out.
6) Transceiver Processing for Fast
Time-Varying Channels - 7 papers
Chairs: Franz
Hlawatsch, Gerald Matz
AuditoriumFranz
Hlawatsch (Vienna University of Technology, Austria)
-
Blind CFO estimation for OFDM with
constant modulus constellations: performance bounds and algorithms
-
Timo Roman
(Helsinki University of Technology, Finland); Andreas Richter
(Helsinki University of Technology, Finland); Visa Koivunen
(Helsinki University of Technology, Finland)
In this
paper, we derive the Cramer-Rao bound for blind carrier
frequency offset (CFO) estimation in orthogonal frequency
division multiplexing (OFDM) with constant modulus
constellations. A blind maximum likelihood CFO estimator is also
proposed. It achieves highly accurate frequency synchronization
with a single OFDM block, regardless of multipath fading and
without the need for null-subcarriers. The approach is thus very
attractive for time and frequency selective channels where the
CFO may be time varying. If additional information is available,
such as a single pilot symbol, maximum likelihood estimates of
channel parameters and transmitted data can be obtained as a
byproduct. Finally, performance bounds are evaluated for several
commonly encountered scenarios.
-
-
Time-Varying Communication Channels:
Fundamentals, Recent Developments, and Open Problems
-
Gerald Matz
(Vienna University of Technology, Austria); Franz Hlawatsch
(Vienna University of Technology, Austria)
In many
modern communication systems, the assumption of a locally
time-invariant (block-fading) channel breaks down (e.g., due to
growing user mobility, increasing data rates, and higher carrier
frequencies). Fast time-varying channels feature significant
Doppler spread (i.e., time selectivity) in addition to delay
spread (frequency selectivity). In this tutorial paper, we
review some basic characterizations and sparse representations (models)
of time-varying channels. We then discuss several approaches
recently proposed for the modeling, estimation, and equalization
of time-varying channels, and we point out some related open
problems and potential research directions.
-
-
Spatial Multiplexing with Linear
Precoding in Time-Varying Channels with Limited Feedback
-
Geert Leus (Delft
University of Technology, The Netherlands); Claude Simon (Delft
University of Technology, The Netherlands); Nadia Khaled
(Interuniversity Micro-Electronics Center (IMEC), Belgium)
Combining
spatial multiplexing with linear unitary precoding allows for
high data rates, but requires a feedback link from the receiver
to the transmitter. We focus on quantizing and feeding back the
precoder itself, since it outperforms quantized channel
feedback. More specifically, we propose a modified precoder
quantization approach that outperforms the conventional one. We
investigate both the linear minimum mean square error (LMMSE)
detector, which minimizes the mean square error (MSE) between
the transmitted and estimated symbols, and the singular value
decomposition (SVD) detector, which is a unitary detector that
aims at diagonalizing the channel matrix. In this context, we
illustrate that the LMMSE detector performs slightly better than
the SVD detector. We also study precoder extrapolation, when the
precoder is only fed back at a limited number of time instances,
as well as a related detector extrapolation scheme for the LMMSE
and SVD detector, when the channel is only known at some
specific time instances. Simulation results illustrate the
efficiency of the proposed extrapolation methods.
-
-
Banded Equalizers for MIMO-OFDM in fast
Time-Varying Channels
-
Luca Rugini
(University of Perugia, Italy); Paolo Banelli (University of
Perugia, Italy)
We propose
low-complexity equalizers for multiple-input multiple-output
(MIMO) orthogonal frequency-division multiplexing (OFDM) systems
in frequency-selective time-varying channels, by extending the
approach we formerly proposed for single-antenna OFDM systems.
Specifically, by neglecting the intercarrier inter-ference (ICI)
coming from faraway subcarriers, we design mini-mum mean-squared
error (MMSE) block linear equalizers (BLE) and MMSE block
decision-feedback equalizers (BDFE) that exploit a band LDL
factorization algorithm. The complexity of the pro-posed banded
equalizers is linear in the number of subcarriers, differently
from conventional MMSE-BLE and MMSE-BDFE char-acterized by a
cubic complexity. We also consider a receiver win-dow designed
to minimize the power of the undesired ICI. Simula-tion results
show that windowing is beneficial in taking under con-trol the
complexity of the proposed equalizers with acceptable
performance loss with respect to the conventional MMSE-BLE and
MMSE-BDFE.
-
-
Estimation of Doubly-Selective Channels
in Block Transmissions
-
Mounir
Ghogho (University of Leeds, United Kingdom); Ananthram Swami (Army
Research Lab., USA)
We propose
to estimate time-varying frequency-selective channels using
data-dependent superimposed training (DDST) and a basis
expansion model (BEM). The proposed method is an extension of
the DDST-based method recently proposed for time-invariant
channels. The superimposed training consists of the sum of a
known sequence and a data-dependent sequence, which is unknown
to the receiver. The data-dependent sequence cancels the effects
of the unknown data on channel estimation. Symbol detection is
performed using MMSE equalization.
-
-
Direct Equalization of Multiuser
Doubly-Selective Channels Based on Superimposed Training
-
Shuangchi He
(Auburn University, USA); Jitendra Tugnait (Auburn University,
USA)
Design of
doubly-selective linear equalizers for multiuser
frequency-selective time-varying communications channels is
considered using superimposed training and without first
estimating the underlying channel response. Both the
time-varying channel as well as the linear equalizers are
assumed to be described by a complex exponential basis expansion
model (CE-BEM). User-specific periodic (non-random) training
sequences are arithmetically added (superimposed) to the
respective information sequences at the transmitter before
modulation and transmission. There is no loss in information
rate. Knowledge of the superimposed training specific to the
desired user and properties of the other training sequences are
exploited to design the equalizers. An illustrative simulation
example is presented.
-
-
Minimum-Energy Bandlimited Time-Variant
Channel Prediction With Dynamic Subspace Selection
-
Thomas Zemen (ftw.
Forschungszentrum Telekommunikation Wien, Austria); Christoph
Mecklenbräuker (FTW, Austria); Bernard Fleury (Aalborg University,
Denmark)
In current
cellular communication systems the time-selective fading process
is highly oversampled. We exploit this fact for time-variant
flat-fading channel prediction by using dynamically selected
predefined low dimensional subspaces spanned by discrete prolate
spheroidal (DPS) sequences. The DPS sequences in each subspace
exhibit a subspace-specific bandwidth matched to a certain
Doppler frequency range. Additionally, DPS sequences are energy
concentrated in a time interval matched to the channel
observation interval. Both properties enable the application of
DPS sequences for minimum-energy (ME) bandlimited prediction.
The dimensions of the predefined subspaces are in the range from
one to five for practical communication systems. The subspace
used for ME bandlimited prediction is selected based on a
probabilistic bound on the reconstruction error. In contrast,
time-variant channel prediction based on non-orthogonal complex
exponential basis functions needs Doppler frequency estimates
for each propagation path which requires high computational
complexity. We compare its performance (using perfectly known
complex exponentials) with that of ME bandlimited prediction
with dynamic subspace selection. In particular we analyze the
mean square prediction error of the two schemes versus the
number of discrete propagation paths.
7-I°) Genomic signal processing - 5 papers
AuditoriumAlfred Hero
(University of Michigan, USA)
-
Dependence Model and Network for
Biomarker Identification and Cancer Classification
-
Peng Qiu
(University of Maryland, College Park, USA); Z. Jane Wang
(University of British Columbia, Canada); K.J. Ray Liu (Department
of Electrical and Computer Engineering, University of Maryland,
USA)
Of
particular interest in this paper is to develop statistical and
modeling approaches for protein biomarker discovery to provide
new insights into the early detection and diagnosis of cancer,
based on mass spectrometry (MS) data. In this paper, we propose
to employ an ensemble dependence model (EDM)-based framework for
cancer classification, protein dependence network reconstruction,
and further for biomarker identification. The dependency
revealed by the EDM reflects the functional relationships
between MS peaks and thus provides some insights into the
underlying cancer development mechanism. The EDM-based
classification scheme is applied to real cancer MS datasets, and
provides superior performance for cancer classification when
compared with the popular Support Vector Machine algorithm. From
the eigenvalue pattern of the dependence model, the dependence
networks are constructed to identify cancer biomarkers.
Furthermore, for the purpose of comparison, a
classification-performance-based biomarker identification
criterion is examined. The dependence-network-based biomarkers
show much greater consistency in cross validation. Therefore,
the proposed dependence-network-based scheme is promising for
use as a cancer diagnostic classifier and predictor.
-
-
A Differential Biclustering Algorithm for
Comparative Analysis of Gene Expression
-
Alain
Tchagang (University of Minnesota, USA); Ahmed Tewfik (Prof.
University of Minnesota, USA)
Convergences and divergences among related organisms (S.cerevisiae
and C.albicans for example) or same organism (healthy and
disease tissues for example) can often be traced to the
differential expression of specific group of genes. Yet,
algorithms to characterize such differences and similarities
using gene expression data are not well developed. Given two
related organisms A and B, we propose here a novel differential
biclustering algorithm, that aims at finding convergent
biclusters that is group of genes with similar functions that
are conserved in A and B, and divergent biclusters that is group
of genes with similar function in A (or B) but which play
different role in B (or A). Uncovering such patterns can
elucidate new insides about how related organisms have evolved
or the role played by some group of genes during the development
of some diseases. Our differential biclustering algorithm
consists of two steps. The first step consists of using a
parallel biclustering algorithm to uncover all qualified
biclusters with coherent evolutions in each set of data. The
second step consists of performing a differential analysis on
the set of biclusters identified in step one, yielding a set of
convergent biclusters and a set of divergent biclusters
-
-
Choosing the design parameters for
protein lysate arrays
-
Andrea
Hategan (Tampere University of Technology, Finland); Ioan Tabus
(University of Tampere, Finland); Jaakko Astola (Tampere
University of Technology, Finland)
Protein
lysate array is a new technology for measuring the relative
expressions of proteins, where the array image provides
information about the concentrations (expressions) of a given
protein for tens of patients or tissues. The array consists of
replicated or serially diluted versions of the biological
samples at several spots. When producing the lysate array the
experimenter has to set several parameters, such as: the
concentration of the sample solution to be printed at a certain
spot, the concentration of the antibody solution, the number of
dilutions, the number of replicates for each biological sample,
and the dilution factor. Having the resulting image of
intensities at all spots one can assume a nonlinear model and
estimate the values of the relative protein expression levels
for all biological samples. In this paper we study how the
obtained model can be used to improve the design of the
experiment, such that if a second lysate array will be produced,
better design parameters will be selected. We propose a
methodology for choosing the design parameters, and illustrate
it with results for several lysate array data sets.
-
-
Spectral Analysis of DNA Sequences by
Entropy Minimization
-
Lorenzo
Galleani (Politecnico di Torino, Italy); Roberto Garello
(Politecnico di Torino, Italy)
Spectral
analysis can be applied to study base-base correlation in DNA
sequences. A key role is played by the mapping between
nucleotides and real/complex numbers. In this paper, we present
a new approach where the mapping is not kept fixed: it is
allowed to vary aiming to minimize the spectrum entropy, thus
detecting the main hidden periodicities. The new technique is
first introduced and discussed through a number of case studies,
then extended to encompass time-frequency analysis.
-
-
A Sequential Monte Carlo Method for Motif
Discovery
-
Kuo-Ching
Liang (Columbia University, ? ); Xiaodong Wang (Columbia
University, USA); Dimitris Anastassiou (Columbia University, USA)
We propose
a sequential Monte Carlo (SMC)-based motif discovery algorithm
that can efficiently detect motifs in datasets containing a
large number of sequences. The statistical distribution of the
motifs and the positions of the motifs within the sequences are
estimated by the SMC algorithm. The proposed SMC motif discovery
technique can locate motifs under a number of scenarios,
including the single-block model, two-block model with unknown
gap length, motifs of unknown lengths, motifs with unknown
abundance, and sequences with multiple unique motifs. The
accuracy of the SMC motif discovery algorithm is shown to be
superior to that of the existing methods based on MCMC or EM
algorithms. Furthermore, it is shown that the proposed method
can be used to improve the results of existing motif discovery
algorithms by using their results as the priors for the SMC
algorithm.
7-II°) Genomic signal processing - 4
papers
AuditoriumAlfred Hero
(University of Michigan, USA)
-
Probabilistic Data Integration and
Visualization for Understanding Transcriptional Regulation
-
Arvind Rao
(University of Michigan, Ann Arbor, USA); Alfred Hero (University
of Michigan, USA); David States (University of Michigan, Ann Arbor,
USA); James Douglas Engel (University of Michigan, Ann Arbor, USA)
In this
paper we propose a manifold embedding methodology to integrate
heterogeneous sources of genomic data for the purpose of
interpretation of transcriptional regulatory phenomena and
subsequent visualization. Using the Gata3 gene as an example, we
ask if it is possible to determine which genes (or their
products) might be potentially involved in its tissue-specific
regulation - based on evidence obtained from various available
data sources. Our approach is based on co-embedding of genes
onto a manifold wherein the proximity of neighbors is influenced
by the probability of their interaction as reported from diverse
data sources - i.e. the stronger the evidence for that gene-gene
interaction, the closer they are.
-
-
Large-scale analysis of the human genome:
from DNA sequence analysis to the modeling of replication in
higher eukaryotes
-
Alain
Arneodo (CNRS-Ecole Normale Suprieure de Lyon, France); Yves D'Aubenton-Carafa
(CGM-CNRS, France); Benjamin Audit (ENS-Lyon, France); Edward
Brodie of Brodie (ENS-Lyon, France); Samuel Nicolay (ENS-lyon,
France); Philipppe St-Jean (ENS-Lyon, France); Claude Thermes (CGM-CNRS,
France); Marie Touchon (CGM-CNRS, France); Cedric Vaillant (genopole,
Evry, France)
We explore
large-scale nucleotide compositional fluctuations along the
human genome through the optics of the wavelet transform
microscope. Analysis of the TA and GC skews reveals the
existence of strand asymmetries associated to transcription
and/or replication. The investigation of 14854 intron-containing
genes shows that both skews display a characteristic step-like
profile exhibiting sharp transitions between transcribed (finite
bias) and non-transcribed (zero bias) regions. As we observe for
7 out of 9 origins of replication experimentally identified so
far, the (AT+GC) skew exhibits rather sharp upward jumps, with a
linear decreasing profile in between two successive jumps. We
describe a multi-scale methodology that allows us to predict
1012 replication origins in the 22 human autosomal chromosomes.
We present a model of replication with well-positioned
replication origins and random termination sites that accounts
for the observed characteristic serrated skew profiles. We
emphasize these putative replication initiation zones as regions
where the chromatin fiber is likely to be more open so that DNA
be easily accessible. In the crowded environment of the cell
nucleus, these intrinsic decondensed structural defects actually
predisposes the fiber to spontaneously form rosette-like
structures that provide an attractive description of genome
organization into replication foci that are observed in
interphase mammalian nuclei.
-
-
An Equivalent Markov Model for Gillespie's
Stochastic Simulation Algorithm for biochemical systems
-
Ronit Bustin
(Tel-Aviv University, Israel); Hagit Messer (Tel-Aviv University,
Israel)
Mathematical/statistical modeling of biological systems is a
desired goal for many years. It aims to be able to accurately
predict the operation of such systems under various scenarios
using computer simulations. In this paper we revisit Gillespie's
Stochastic Simulation Algorithm for biochemical systems and we
suggest an equivalent Markov Model for it. We show that under
certain conditions it is a first order homogenous Markov process
and we analyze these conditions. Our suggested model can be used
to simulate the probability density function of a biochemical
processes which, in turn, can be used for applying statistical
signal processing and information theory tools on them.
8) Distributed signal processing in sensor
networks - 7 papers
Chairs: Sergio
Barbarossa, Ananthram Swami
Adua 2Sergio BARBAROSSA
(University of Rome La Sapienza", Italy)
-
Hypothesis Testing Over a Random Access
Channel in Wireless Sensor Networks
-
Elvis
Bottega (University of Padova, Italy); Petar Popovski (Aalborg
University, Denmark); Michele Zorzi (Universitŕ degli Studi di
Padova, Italy); Hiroyuki Yomo (CTIF, Aalborg University, Denmark);
Ramjee Prasad (Aalborg University, Denmark)
In the
design of the communication protocols for wireless sensor
networks a specific requirement emerges from the fact that the
data contained in an individual sensor is not important per se,
but its significance is instantiated with respect to the
contribution to the overall sensing task and the decision fusion.
Therefore, the communication protocols should be
application-aware and operate by reckoning the utility of the
carried data. In this paper we consider the problem of
hypothesis testing at the fusion center (sink) when all the
sensors communicate with the sink via a random access channel.
Each sensor contains a binary information 0 (event occurred) or
1 (event did not occur). In a traditional protocol design, an
existing random--access protocol is used by which the sink
collects the data from all sensors and subsequently makes the
decision through majority voting over the received data. In this
paper, we propose approaches for joint design of the
communication and the decision fusion for the application of
hypothesis testing. The fusion center terminates the data
gathering through the random access channel as soon as it can
make sufficiently reliable decision based on the data received
so far. We describe two instances of the protocols, where the
total number of sensors $N$ is known and not known, respectively.
Our results show that the proposed approaches provide optimized
performance in terms of time, energy and reliability.
-
-
Reducing Power Consumption in a Sensor
Network by Information Feedback
-
Mikalai
Kisialiou (University of Minnesota, USA); Zhi-Quan Luo (University
of Minnesota, USA)
We study
the role of information feedback for the problem of distributed
signal tracking/estimation using a sensor network with a fusion
center. Assuming that the fusion center has sufficient energy to
reliably feed back its intermediate estimates, we show that the
sensors can substantially reduce their power consumption by
using the feedback information in a manner similar to the
stochastic approximation scheme of Robbins-Monro. For the
problem of tracking an autoregressive source or estimating an
unknown parameter, we quantify the total achievable power saving
(as compared to the distributed schemes with no feedback), and
provide numerical simulations to confirm the theoretical
analysis.
-
-
Clustering in Distributed Estimation with
Dependent Observations
-
Sung-Hyun
Son (Princeton University, USA); Sanjeev Kulkarni (Princeton
University, USA); Stuart Schwartz (Princeton University, USA)
A wireless
sensor network with dependent observations is considered to
study the effects of clustering on the parameter estimation
problem. The set of sensors is partitioned in such a way that
the intracluster sensor observations are spatially correlated
while the intercluster sensor observations are independent. The
size of the cluster allows flexibility in selecting the
magnitude of spatial correlation which ranges from one sensor
per cluster, (i.e., independent observations), to all sensors in
one cluster, (i.e. dependent observations). From an energy point
of view, sending all the local data to the fusion center is the
most costly, but leads to optimum performance results since all
the dependencies are taken into account. From an estimation
accuracy point of view, sending only parameter estimates and
associated quality measures is the least accurate, but is the
most parsimonious in terms of communication costs. Hence, this
tradeoff between the cluster size and the estimation accuracy is
explored. Various topologies and communication protocols are
studied where both communication costs and estimation accuracy
are optimized.
9)
Bayesian Methods for Inverse Problems in Image and Signal Processing
- 7 papers
Chair:
Nikolaos Galatsanos
Sala VerdeNikolaos
Galatsanos (University of Ioannina, Greece)
-
Analysis versus Synthesis in Signal
Priors
-
Ron
Rubinstein (Technion, Israel Institute of Technology, Israel);
Michael Elad (Technion, Israel); Peyman Milanfar (University of
California, Santa Cruz, Canada)
The
concept of prior probability for signals plays a key role in the
successful solution of many inverse problems. Much of the
literature on this topic can be divided between analysis-based
and synthesis-based priors. Analysis-based priors assign
probability to a signal through various forward measurements of
it, while synthesis-based priors seek a reconstruction of the
signal as a combination of atom signals. In this paper we
describe these two prior classes, focusing on the distinction
between them. We show that although when reducing to the
complete and under-complete formulations the two become
equivalent, in their more interesting over-complete formulation
the two types depart. Focusing on the L1 denoising case, we
present several ways of comparing the two types of priors,
establishing the existence of an unbridgeable gap between them.
-
-
Adaptive Bayesian/Total-Variation Image
Deconvolution: A Majorization-Minimization Approach
-
José
Bioucas-Dias (Instituto Superior Técnico, Portugal); Mario
Figueiredo (Instituto Superior Técnico, Portugal); Joăo Oliveira (Instituto
Superior Técnico, Portugal)
This paper
proposes a new algorithm for total variation (TV) image
deconvolution under the assumptions of linear observations and
additive white Gaussian noise. By adopting a Bayesian point of
view, the regularization parameter, modeled with a Jeffreys'
prior, is integrated out. Thus, the resulting crietrion adapts
itself to the data and the critical issue of selecting the
regularization parameter is sidestepped. To implement the
resulting criterion, we propose a {\em majorization-minimization}
approach, which consists in replacing a difficult optimization
problem with a sequence of simpler ones. The computational
complexity of the proposed algorithm is O(N) for finite support
convolutional kernels. The results are competitive with recent
state-of-the-art methods.
-
-
Hirarchical Markovian Models for 3D
Computed Tomography in Non Destructive Testing Applications
-
Ali
Mohammad-Djafari (Centre national de la recherche scientifique (CNRS),
France); Lionel Robillard (EDF, France)
Computed
Tomography (CT) has become an usual technic in Non Destructive
Testing (NDT) applications, in particular in detection and
characterization of defaults in metalic objects. One of the
characteristics of such applications is that, in general the
number and angles of of projections are very limited, but at the
other hand, we know a priori the number of the kind of materials
we can found, mainly metal and air or metal, air and a composite
material. In this work, we first propose a particular
hierarchical Markov-Potts a priori model which takes into
account for the specificty of the NDT CT. Then, we give details
of a Bayesian estimation computation based on MCMC and EM
technics. Finally, we show the performances of the proposed 3D
CT reconstruction method with a very limited number and angles
of projections with very low signal to noise ratio simulating a
real application of NDT in power plants industry.
-
-
Hierarchical Bayesian Super Resolution
Reconstruction of Multispectral Images
-
Rafael
Molina (Universidad de Granada, Spain); MIguel Vega (University of
Granada, Spain); Javier Mateos (University of Granada, Spain);
Aggelos K. Katsaggelos (Northwestern University, USA)
In this
paper we present a super resolution Bayesian methodology for
pansharpening of multispectral images which: a) incorporates
prior knowledge on the expected characteristics of the
multispectral images, b) uses the sensor characteristics to
model the observation process of both panchromatic and
multispectral images, c) includes information on the unknown
parameters in the model, and d) allows for the estimation of
both the parameters and the high resolution multispectral image.
Using real data, the pansharpened multispectral images are
compared with the images obtained by other parsharpening methods
and their quality assessed both qualitatively and quantitatively.
-
-
Variational Bayesian Blind Image
Deconvolution Based on a Sparse Kernel Model for the Point Spread
Function
-
Dimitris
Tzikas (University of Ioannina, Greece); Aristidis Likas
(University of Ioannina, Greece); Nikolaos Galatsanos (University
of Ioannina, Greece)
In this
paper we propose a variational Bayesian algorithm for the blind
image deconvolution problem. The unknown point spread function
(PSF) is modeled as a sparse linear combination of kernel basis
functions. This model offers an effective mechanism to estimate
for the first time both the support and the shape of the PSF.
Numerical experiments demonstrate the effectiveness of the
proposed methodology.
-
-
Adaptive regularization of noisy linear
inverse problems
-
Lars Kai
Hansen (Technical University of Denmark, Denmark); Kristoffer
Madsen (Tecnical University of Denmark, Denmark); Tue
Lehn-Schioler (Technical University of Denmark, Denmark)
In the
Bayesian modeling framework there is a close relation between
regularization and the prior distribution over parameters. For
prior distributions in the exponential family, we show that the
optimal hyperparameter, i.e., the optimal strength of
regularization, satisfies a simple relation: The expectation of
the regularization function, takes the same value in the
posterior and prior distribution. We present three examples: Two
simulations and application in fMRI neuroimaging.
-
-
A Perceptual Bayesian Estimation
Framework and its Application to Image Denoising
-
Javier
Portilla (Universidad de Granada, Spain)
We present
a generic Bayesian framework for signal estimation that
incorporates into the cost function a perceptual metric. We
apply this framework to image denoising, considering additive
noise of known density. Under certain assumptions on the way
local differences in visual responses add up into a global
perceptual distance, we obtain analytical solutions that exhibit
interesting theoretical properties. We demonstrate through
simulations, using an {\em infomax} non-linear perceptual
mapping of the input and a local Gaussian model, that in the
absence of a prior the new solutions provide a significant
improvement on the visual quality of the estimation. Furthermore,
they also improve in Mean Square Error terms w.r.t. their
non-perceptual counterparts.
-
-
11) Cross-layer Optimization for Wireless
Communication Systems - 7 papers
Adua
3 Holger Boche (Fraunhofer Institute
for Telecommunications HHI, Germany)
-
Sub-carrier SNR Estimation at the
Transmitter for Reduced Feedback OFDMA
-
Patrick
Svedman (Royal Institute of Technology, Sweden); David Hammarwall
(Royal Institute of Technology, Sweden); Bjorn Ottersten (Royal
Institute of Technology, Sweden)
In
multiuser OFDMA FDD systems with resource allocation based on
the instantaneous channel quality of the users, the feedback
overhead can be very large. In this paper, a method to
significantly reduce this feedback is proposed. The idea is to
let the users feed back the channel quality (the SNR in this
paper) of only a sub-set of their strongest sub-carriers. The
SNRs on the other sub-carriers are instead estimated from the
fed back values. We derive the MMSE estimator of the SNR of a
sub-carrier, which uses two fed back SNRs as input. As a
comparison, we also study the performance of the LMMSE estimator
as well as spline interpolation. Numerical results show that the
LMMSE estimator tends to underestimate the SNR compared to the
other two estimators, whereas the interpolation tends to
overestimate the SNR. System simulations including adaptive
modulation and packet losses indicate that the MMSE estimator is
the best choice in practice.
-
-
Distributed Algorithms for Maximum
Throughput in Wireless Networks
-
Yufang Xi (Yale
University, USA); Edmund Yeh (Yale University, USA)
The
Maximum Differential Backlog (MDB) control policy of Tassiulas
and Ephremides has been shown to adaptively maximize the stable
throughput of multi-hop wireless networks with random traffic
arrivals and queueing. The practical implementation of the MDB
policy in wireless networks with mutually interfering links,
however, requires the development of distributed optimization
algorithms. Within the context of CDMA-based multi-hop wireless
networks, we develop a set of node-based scaled gradient
projection power control algorithms which solves the MDB
optimization problem in a distributed manner using low
communication overhead. As these algorithms require time to
converge to a neighborhood of the optimum, the implementation of
the MDB policy must be done with delayed queue state information.
For this, we show that the MDB policy with delayed queue state
information remains throughput optimal.
-
-
Autonomous QoS Control for Wireless Mesh
and Ad-hoc Networks - the Generalized Lagrangean Approach
-
Marcin
Wiczanowski (Technical University of Berlin, Germany); Slawomir
Stanczak (Fraunhofer German-Sino Lab for Mobile Comm., Germany);
Holger Boche (Fraunhofer Institute for Telecommunications HHI,
Germany)
We
consider the combined problem of performance optimization and
interference control in wireless mesh and ad-hoc networks.
Relying on the specific construction of the generalized
Lagrangean function we propose a simple primal-dual
unconstrained iteration providing convergence to a (local)
optimum under arbitrary performance objectives. We present a
decentralized implementation of such routine in linear networks.
-
-
A framework for resource allocation in
OFDM broadcast systems
-
Gerhard
Wunder (Heinrich-Hertz-Institut, Germany); Thomas Michel (German-Sino
Mobile Communications Institute (MCI), Germany); Chan Zhou (Mobile
Communication Lab for Mobile Communications MCI, HHI, Germany)
In this
paper we consider resource allocation for OFDM broadcast
channels (BC) where we introduce several scheduling policies in
an ideal information-theoretic context and analyze their
performance in terms of throughput, stability and delay
dependent on system parameters such as user numbers and channel
parameters. We provide algorithms to solve the stated scheduling
problems where we use Langrangian and duality theory. These
solutions can be used as a general benchmark for specific
approaches and they also provide some intuition for good
suboptimal solutions. Additionally, all these strategies are
compared to a practical setup tested in a complete simulation
chain (physical and medium access layer) according to the 3GPP
HSDPA specification.
-
-
On the interplay between scheduling, user
distribution, CSI, and performance measures in cellular downlink
-
Eduard
Jorswieck (Royal Institute of Technology (KTH), Sweden); Mats
Bengtsson (Royal Institute of Technology, Sweden); Bjorn Ottersten
(Royal Institute of Technology, Sweden)
The
cross-layer design of future communication systems jointly
optimizes multiple network layers with the goal of boosting the
system wide performance. This trend brings together the physical
and the medium access layers. For the joint optimization of
these two lowest layers, it is necessary to understand and
relate their terms and concepts. In this paper, we study the
interplay between four terms, namely channel state information
from link-level, scheduling and user distribution from system
level, and different performance measures from both levels. The
envisaged scenario is the cellular downlink transmission. The
average sum rate describes the long-term performance from a
system perspective. The optimal scheduling policy as well as the
impact of the user distribution can be clearly characterized as
a function of the channel state information (CSI). In contrast,
the short-term system performance which is described by the
outage sum rate, shows a varying behavior in terms of the
optimal scheduling policy and as a function of the user
distribution. The analysis is performed by employing
Majorization theory for comparing different user distributions.
Three different CSI scenarios, namely the uninformed base, the
perfectly informed base, and the base with covariance knowledge
are studied. Finally, the extension to two less well known
performance measures, the maximum throughput and the
delay-limited sum rate is addressed.
-
-
Cross-layer Solutions to Performance
Problems in VoIP over WLANs
-
Federico
Maguolo (University of Padova, Italy); Francesco De Pellegrini (Universita`
di Padova, Italy); Andrea Zanella (University of Padova, Italy);
Michele Zorzi (University of Padova, Italy)
The design
of WLANs was meant to extend Ethernet LANs in the most
transparent way, but no particular mechanism was deployed in
order to support real-time applications natively. At present
VoIP calls are becoming customary, and IEEE802.11 WLANs must
face the provision of guaranteed quality of service. In practice,
QoS should be provided somehow a posteriori on top of the
existing standard. In this paper, we address some concerns on
the efficiency of WLANs for VoIP provision already remarked in
literature and analyze possible solutions to increase the voice
capacity of DCF IEEE802.11 WLANs. We consider two candidate
solutions, the VA [1] and the M-M [2] cross-layer schemes. The
efficiency of such mechanisms is evaluated in order to assess
the performance gain compared to existing solutions. We provide
extensive simulation results, proving that the advantage is
signifcant, while requiring minor changes compared to the
current IEEE802.11 standard.
-
-
Coordination and resilience in wireless
adhoc and sensor networks
-
Leandros
Tassiulas (University of Thessaly, Greece)
12-I°) MIMO Channel Modelling, Emulation
and Sounding - 5 papers
AuditoriumPeter Grant (Edinburgh
School of Engineering and Electronics, United Kingdom)
-
A review of radio channel sounding
techniques
-
David
Laurenson (The University of Edinburgh, United Kingdom); Peter
Grant (Edinburgh School of Engineering and Electronics, United
Kingdom)
This short
paper will introduce the key approaches that have been adopted
for channel sounding and describe systems that have been
reported to date for measuring indoor and outdoor radio channels
in the 1-5 GHz range of operating frequencies.
-
-
Performance Verification of MIMO Concepts
using Multi-Dimensional Channel Sounding
-
Christian
Schneider (Technische Universität Ilmenau, Germany); Uwe Trautwein
(TeWiSoft, Germany); Reiner Thomae (University of Ilmenau, Germany);
Walter Wirnitzer (MEDAV GmbH, Germany)
The
advances in multi-dimensional channel-sounding techniques make
it possible to evaluate performances of radio multiple access
and signal processing schemes under realistic propagation
conditions. This paper focuses on the methodology how recorded
impulse response data gathered through multidimensional channel
sounding field measurements can be used to evaluate link- and
system-level performances of the multiple-input multiple-output
(MIMO) radio access schemes. The method relies on offline
simulations. It can be classified in between the performance
evaluation using some predefined channel models and the
evaluation in field experiments using a set of prototype
hardware. New aspects for the simulation setup are discussed,
which are frequently ignored when using simpler model-based
evaluations. Example simulations are provided for an iterative
("turbo") MIMO equalizer concept. The dependency of the
achievable bit error rate performance on the spatial-temporal
propagation characteristics and on the variation in some system
design parameters is shown. Although in many of the considered
constellations turbo MIMO equalization appears feasible in real
field scenarios, there exist cases with poor performance as well,
indicating that in practical applications link adaptation of the
transmitter and receiver processing to the environment is
necessary.
-
-
Characterization of MIMO Channels for
Handheld Devices in Personal Area Networks at 5 GHz
-
Johan
Karedal (Lund Univ., Sweden); Anders Johansson (Lund University,
Sweden); Fredrik Tufvesson (Lund University, Sweden); Andreas
Molisch (Mitsubishi Electric Research Laboratory, USA)
In this
paper we analyze the properties of MIMO channels for personal
area networks (PANs). Such channels differ from propagation
channels in wide-area networks due to several reasons: (i) the
environments in which the systems operate are different, (ii)
the mobility models and ranges are different, (iii) the
influence from human presence in the environment is different.
In this paper, we present results from a measurement campaign
for PAN channels between two handheld devices. The measurements
are conducted over distances of 1-10 m using two handheld
four-element antenna devices. For each distance, a number of
channel realizations are obtained by moving the devices over a
small area, and by rotating the persons holding the devices. We
find that the correlation between the antenna elements is low.
The small-scale statistics of the amplitude are well described
by the Rayleigh distribution in many cases, but the effects of
shadowing by the body of the operator can lead to different
statistics.
-
-
A Simple Approach to MIMO Channel
Modelling
-
Rafal Zubala
(Warsaw University of Technology, Poland); Hubert Kokoszkiewicz (Warsaw
University of Technology, Poland); Martijn Kuipers (IT / IST-TUL,
Portugal); Luis Correia (IST - Tech. Univ. Lisbon, Portugal)
A
semi-statistical MIMO radio channel model is described, adequate
for analysing multi-user environments, by simulating the
channels between different users at the radio propagation level.
The model is capable of simulating MIMO links between users, by
allowing multiple antennas at mobile terminals and/or base
stations. Results are shown for the influence of antenna spacing
on MIMO capacity gain. For pico- and micro-cells, an increase in
the number of antennas has a larger impact on capacity gain
compared to macro-cells. Using the Geometrically Based Single
Bounce Channel Model for micro-cell scenarios, a 20% variation
in performance is obtained, depending on the orientation of
antennas of both transmitter and receiver. For the macro-cell, a
similar variation is seen, but only for the orientation of base
station antennas.
-
-
Enhanced Tracking of Radio Propagation
Path Parameters Using State-Space Modeling
-
Jussi Salmi
(Helsinki University of Technology, Finland); Andreas Richter
(Helsinki University of Technology, Finland); Visa Koivunen
(Helsinki University of Technology, Finland)
Future
wireless communication systems will exploit the rich spatial and
temporal diversity of the radio propagation environment. This
requires new complex channel models, which need to be verified
by real-world channel sounding measurements. In this context the
reliable estimation and tracking of the model parameters from
measurement data is of particular interest. In this paper, we
build a state-space model, and track the propagation parameters
with the Extended Kalman Filter in order to capture the dynamics
of the channel parameters in time. We then extend the model by
considering first order derivatives of the geometrical
parameters, which enhances the tracking performance due to
improved prediction and robustness against shadowing and fading.
The model also includes the effect of distributed diffuse
scattering in radio channels. The issue of varying state
variable dimension, i.e., the number of propagation paths to
track, is also addressed. The performance of the proposed
algorithms is demonstrated using both simulated and measured
data.
12-II°) MIMO Channel Modelling, Emulation
and Sounding - 4 papers
AuditoriumPeter Grant (Edinburgh
School of Engineering and Electronics, United Kingdom)
-
Modelling and Manipulation of
Polarimetric Antenna Beam Patterns via Spherical Harmonics
-
Giovanni Del
Galdo (Ilmenau University of Technology, Germany); Jörg Lotze (Ilmenau
University of Technology, Germany); Markus Landmann (Ilmenau
University of Technology, Germany); Martin Haardt (Ilmenau
University of Technology, Germany)
Measured
antenna responses, namely their beam patterns with respect to
the vertical and horizontal polarizations, play a major role in
realistic wireless channel modeling as well as in parameter
estimation techniques. The representations commonly used suffer
from drawbacks introduced by the spherical coordinate system
which is affected by two knots at the poles. In general, all
methods which describe the beam pattern with a matrix fail in
correctly reproducing its inherent spherical symmetry. In this
contribution we propose the use of the Spherical Fourier
Transformation (SFT) which allows the description of the beam
pattern via spherical harmonics. This mathematical tool, well
known in other fields of science, is rather new to wireless
communications. The main applications of the SFT include the
efficient description of a beam pattern, noise filtering, the
precise interpolation in the spherical Fourier domain, and the
possibility to obtain an equivalent description of the beam
pattern for an arbitrary coordinate system. The latter allows us
to improve an existing 2-D FFT based technique: the Effective
Aperture Distribution Function (EADF).
-
-
Distributed UWB MIMO Sounding for
Evaluation of Cooperative Localization Principles in Sensor
Networks
-
Rudolf Zetik
(Technical University Ilmenau, Germany); Jürgen Sachs (TU Ilmenau,
Germany); Reiner Thomä (TU-Illmenau, Germany)
We
describe architecture, design, and a novel application of a
real-time MIMO UWB channel sounder. The sounder is applied for
evaluating of localization principles in distrib-uted sensor
networks that are based on UWB radio technol-ogy. We assume an
application scenario without any sup-porting infrastructure as
it may occur in emergency situa-tions such as fire disasters,
earthquakes or terror attacks. At first we discuss the
deployment scenario and signal process-ing principles applied
for cooperative sensor node localiza-tion and imaging of the
propagation environment. Then, we describe the architecture of
the UWB MIMO channel sounder. Finally, a measurement example is
demonstrated
-
-
System-level performance evaluation of
MMSE MIMO turbo equalization techniques using measurement data
-
Mariella
Särestöniemi (University of Oulu, Finland); Tadashi Matsumoto (CWC
- Oulu, Finland); Christian Schneider (Technische Universität
Ilmenau, Germany); Reiner Thomä (TU-Illmenau, Germany)
In this
paper, system-level performance of MMSE turbo MIMO equalization
techniques is evaluated in realistic scenarios. Soft
cancellation and minimum mean squared error filtering (SC/MMSE)
turbo equalization and its complexity reduced version, turbo
equalized diversity, is considered. Furthermore, another version
of equalized diversity, turbo equalized diversity with common SC/MMSE,
which exploits the transmit diversity and coding gain through
the cross-wise iterations over the decoding branches, is
evaluated. The multi-dimensional channel sounding measurement
data used for the simulations consists of snapshots measured in
different channel conditions in terms of spatial and temporal
properties. The system-level assessment is in terms of outage
probabilities of the performance figures such as bit and frame
error rates obtained by evaluating their cumulative probability
densities using the field measurement data. It is found that the
receivers considered in this paper can all provide reasonable
system-level performance. However, turbo equalized diversity
receiver is slightly more sensitive to the channel conditions
than the original SC/MMSE equalizer. It is also found that the
performance gain obtained from the cross-wise iteration over the
decoding branches in the turbo equalized diversity with common
SC/MMSE technique is significant.
-
-
Widely Linear MMSE Transceiver for
Real-Valued Sequences over MIMO Channel
-
Davide
Mattera (Universitŕ degli Studi di Napoli Federico II, Italy);
Luigi Paura (Universitŕ di Napoli Federico II, Italy); Fabio
Sterle (University of Naples Federico II, Italy)
Joint
design of the precoder and the decoder (say, transceiver) for
multiple-input/multiple-output (MIMO) channels is considered
and, in particular, the already existing procedure for the
design of the linear transceiver according to the
minimum-mean-square-error (MMSE) criterion is extended to the
more general case where the transceiver resorts to widely linear
(WL) processing rather than linear one. WL filters linearly and
independently process both the real and the imaginary parts of
the input signals, and they are usually employed in order to
trade-off a limited increase in the computational complexity
with performance gains when the input signals are circularly
variant. For this reason, we propose to resort to WL processing
in the synthesis of the MIMO transceiver when real-valued data
streams have to be transmitted. The performance analysis shows
significant performance advantages of the proposed WL-MMSE MIMO
transceiver with respect to the linear one.
13-I°) Multi-user MIMO Communications - 7
papers
Chair: C. F.
Mecklenbrŕuker
Sala VerdeChristoph
Mecklenbraeuker (FTW, Austria)
-
Linear receiver interfaces for multiuser
MIMO communications
-
Alessandro
Nordio (Politecnico di Torino, Italy); Giorgio Taricco
(Politecnico di Torino, Italy)
We
consider the uplink of a DS-CDMA wireless communication system
with multiple users equipped with several transmit antennas. We
assume that a multiple-antenna subsystem is added to an existing
multiuser detector and we compare the performance of this
receiver and that of an optimum receiver accounting for both
spatial and multiple-access interference simultaneously. In the
former case we say that the receiver is separate whereas in the
latter we say that the receiver is joint. Several classes of
separate and joint linear receivers are considered and their
performance is evaluated asymptotically and by simulation.
-
-
Multiuser detection using random-set
theory
-
Ezio
Biglieri (Universitat Pompeu Fabra, Barcelona, Spain); Marco Lops
(University of Cassino, Italy)
In mobile
multiple-access communications, not only the location of active
users, but also their number varies with time. In typical
analyses, multiuser detection theory is developed under the
assumption that the number of active users is constant and known
at the receiver, and coincides with the maximum number of users
entitled to access the system. This assumption is often overly
pessimistic, since many users might be inactive at any given
time, and detection under the assumption of a number of users
larger than the real one may impair performance. This paper
undertakes a different, more general approach to the problem of
identifying active users and estimating their parameters and
data in a dynamic environment where users are continuously
entering and leaving the system. Using a mathematical tool known
as Random Set Theory, we derive Bayesian-filter equations which
describe the evolution with time of the a posteriori probability
density of the unknown user parameters, and use this density to
derive optimum detectors.
-
-
Subcarrier Allocation in a Multiuser MIMO
Channel Using Linear Programming
-
Ari Hottinen
(Nokia Research Center, Finland); Tiina Heikkinen (MTT Economic
Research, Finland)
In this
paper, we apply specialized linear programming algorithms in
assigning users to orthogonal frequency channels or subcarriers
in a channel-aware MIMO-OFDMA system. Efficient optimization
techniques enable total utility (e.g. downlink capacity)
maximization in polynomial time in the presence of strict
fairness constraints.
-
-
Efficient Vector Perturbation in
Multi-Antenna Multi-User Systems Based on Approximate Integer
Relations
-
Dominik
Seethaler (Institute of Communications and Radio-Frequency
Engineering, Vienna University of Technology, Austria); Gerald
Matz (Vienna University of Technology, Austria)
Approximate vector perturbation techniques assisted by LLL
lattice reduction (LR) can exploit all the diversity that is
available in multi-user multi-antenna broadcast systems. However,
the required computational complexity of LLL-LR can be quite
large. In this paper, we propose a much simpler and much more
efficient LR algorithm than LLL. This LR technique is based on
Brun's algorithm for finding approximate integer relations (IRs).
The link between LR and IRs is established by considering poorly
conditioned channels with a single small singular value.
Simulation results show that our scheme can achieve large (but
bot full) diversity at a fraction of the complexity required for
LLL-assisted vector perturbation.
-
-
Iterative Transceiver Optimization for
Linear Multiuser MIMO Channels with MMSE Requirements
-
Martin
Schubert (Fraunhofer German-Sino Lab for Mobile Communications MCI,
Germany); Shuying Shi (Fraunhofer German-Sino Lab for Mobile
Communications MCI, Germany); Holger Boche (Fraunhofer Institute
for Telecommunications HHI, Germany)
We address
the problem of jointly optimizing linear transmit and receive
filters for a multi-user MIMO system, under the assumption that
all users have individual Minimum- Mean-Square-Error (MMSE)
requirements. Each user can perform spatial multiplexing with
several data streams (layers). All users and layers are coupled
by interference, so the choice of filters is intricately
interwoven with the power allocation strategy. Design goal is
power minimization under MMSE constraints. This results in
non-convex problem formulations, for which we propose
computationally-efficient iterative algorithms. The iteration
consists of alternating optimization of powers, transmit filters
and receive filters. We prove that the total required power
obtained by the algorithm is monotonically decreasing and
converges to a limit.
-
-
Transmit Correlation-Aided Opportunistic
Beamforming and Scheduling
-
Marios
Kountouris (France Telecom R&D, France); David Gesbert (Eurecom
Institute, France); Lars Pittman (Norwegian Univ. of Science &
Technology, Norway)
The
problem of joint opportunistic scheduling and beamforming for
multiuser systems exploiting partial channel state information
at the transmitter (CSIT) is addressed here. We show that useful
information relevant to the scheduler lies untapped in the
long-term statistical information of users' channels, which is
easily acquired either by uplink/downlink reciprocity of the
second-order statistics or via very low rate feedback. We show
how statistical channel knowledge can be efficiently combined
with instantaneous-but-partial CSIT to derive a channel estimate
for the downlink of multiuser correlated MIMO systems. This
estimate can in turn be exploited for user selection as well as
for the design of the multiuser beamforming matrix. Performance
evaluation shows the capacity gain of this type of approach over
conventional opportunistic schemes in various settings.
-
-
A reduced complexity MIMO Broadcast
scheme: a way between opportunistic and dirty paper implementation
-
Nizar Zorba
(Telecommunications Technological Center of Catalonia (CTTC),
Spain); Ana I. Perez-Neira (Universitat Politecnica de Catalunya,
Spain); Miguel Angel Lagunas (Telecommunications Technological
Center of Catalonia, Spain)
Departing
from the opportunistic schemes in Multiuser Broadcast MIMO
schedulers, practical transmission techniques to get closer to
the channel capacity are proposed for the outdoor urban
scenario. By considering the Spatial Power Density function of
the arriving signal, the paper develops different setups based
on the quantity of available Channel State Information at the
transmitter side (CSIT). In a first approach, Signal to Noise
Interference Ratio (SNIR) feedback scenario is considered, but
to further decrease the gap between the channel capacity and the
proposed scheme, the paper suggests that only the selected users
are asked to provide their full CSIT to the transmitter side.
The goal is to always keep a small load on the feedback link
while at the same time providing almost all of the benefits of
full CSIT scenarios. The proposed schemes are compared via
simulations with other possible transmission strategies in terms
of system sum rate.
13-II°) Multi-user MIMO Communications - 5
papers
Chair: C. F.
Mecklenbrŕuker
Sala Verde
-
Transmit and Receive Antenna Subset
Selection for MIMO SC-FDE in Frequency Selective Channels
-
Andreas
Wilzeck (University Duisburg-Essen, Germany); Patrick Pan
(University Duisburg-Essen, Germany); Thomas Kaiser (University of
Duisburg-Essen, Germany)
Antenna
(subset) selection is a feasible scheme to reduce the hardware
complexity of Multiple-Input Multiple-Output (MIMO) systems.
Studies of antenna selection schemes are typically based on
channel capacity optimizations employing frequency flat channel
models, which are inconsistent with MIMO systems employing
spatial-multiplexing. Such systems aim to offer a high data-rate
transmission, so that the channel is of frequency selective
nature. In this contribution we study antenna subset selection
at transmitter- and receiver-side for theMIMO Single Carrier (SC)
scheme with Frequency Domain Equalization (FDE) in frequency
selective channels. As alternative selection metric the signal
quality of the MIMO equalizer output is used.
-
-
Non-Linear Precoding for MIMO Multi-User
Downlink Transmissions with different QoS requirements
-
Luca Sanguinetti (University of
Pisa, Italy); Michele Morelli (University of Pisa, Italy)
An
efficient non-linear pre-filtering technique based on
Tomlinson-Harashima pre-coding (THP) has recently been proposed
by Liu and Krzymien for multiple antenna multiuser systems. The
algorithm is based on the Zero-Forcing (ZF) criterion and
assumes a number of transmit antennas equals to the number of
active users. In contrast to other methods, it ensures a fair
treatment of the active users providing them the same
signal-to-noise ratio. In multimedia applications, however,
several types of information with different quality-of-service (QoS)
must be supported. Motivated by the above problem, in the
present work we design a ZF THP-based pre-filtering algorithm
for multiple antenna multi-user networks in which the base
station allocates the transmit power according to the QoS
requirement of each active user. In doing so, we consider a
system in which the number of active users may be less than the
number of transmit antennas. As we will see, in such a case
there exists an infinite number of solutions satisfying the ZF
criterion. We address the problem of finding the best using as
optimality criterion the maximization of the signal-to-noise
ratios at all mobile terminals.
-
-
Levenberg-Marquardt Computation of the
Block Factor Model for Blind Multi-user Access in Wireless
Communications
-
Dimitri Nion
(ETIS, UMR 8051 (CNRS, ENSEA, UCP), France); Lieven de LATHAUWER
de LATHAUWER (E.E. Dept. (ESAT) - SCD-SISTA, Belgium)
In this
paper, we present a technique for the blind separation of
DS-CDMA signals received on an antenna array, for a multi-path
propagation scenario with Inter-Symbol-Interference. Our method
relies on a new third-order tensor decomposition, which is a
generalization of the parallel factor model. We start with the
observation that the temporal, spatial and spectral diversities
give a third-order tensor structure to the received data. This
tensor is then decomposed in a sum of contributions, where each
contribution fully characterizes one user. We also present an
algorithm of the Levenberg-Marquardt type for the calculation of
this decomposition. This method is faster than the alternating
least squares algorithm previously used.
-
-
A Selective Beamforming Strategy for
Multi-User MIMO Communications
-
Mirette
Sadek (University of California, Los Angeles, USA); Alireza
Tarighat (University of California. Los Angeles (UCLA), USA); Ali
Sayed (University of California, Los Angeles, USA)
The paper
develops a dynamic antenna scheduling strategy for downlink MIMO
communications, where the transmitted signal for each user is
beamformed towards a selected subset of receive antennas at this
user. It is shown in this paper both analytically and through
simulations that increasing the number of antennas at one user
degrades the SINR performance of other users in the network.
This fact is then exploited to improve the systems performance
in terms of target SINR outage probability for each user. Using
the SINR outage criterion, allows us to lower the number of
targeted antennas at a particular user if the user is already
meeting its target SINR. By doing so, other users in the network
originally below their target SINR can achieve their target SINR
as well. In other words, the antenna scheduling schemes aims at
maximizing the number of users meeting their target SINR values
by dynamically changing the active antenna sub-sets for every
user.
-
-
Linear Detectors for multi-user MIMO
systems with correlated spatial diversity
-
Laura
Cottatellucci (ftw.-Forschungszentrum Telekommunikation Wien,
Austria); Ralf Mueller (Norwegian University of Science and
Technology, Norway); Merouane Debbah (Institut Eurecom, France)
A
multiuser CDMA systems with both the transmitting and the
receiving sites equipped with multiple antenna elements is
considered. The multiuser MIMO channel is correlated at the
transmitting and the receiving sites. Multistage detectors
achieving near-linear MMSE performance with a complexity order
per bit linear in the number of users are proposed. The large
system performance is analyzed in a general framework including
any multiuser detector that admits a multistage representation.
The performance of this large class of detectors is independent
of the channel correlation at the transmitter. It depends on the
direction of the channel gain vector of the user of interest if
the channel gains are correlated.
14-I°) MIMO Transmission Techniques - 5
papers
Adua 2Wolfgang Utschick
(Munich University of Technology, Germany)
-
Design of robust linear dispersion codes
based on imperfect CSI for ML receivers
-
Svante
Bergman (KTH, Sweden); Bjorn Ottersten (Royal Institute of
Technology, Sweden)
This paper
concern the design of codes for multi-input multi-output
communication systems. The transmission scheme utilize imperfect
channel state information (CSI) in the design, assuming
maximum-likelihood detection is employed at the receiver. It is
argued that channel diagonalizing codes are not robust to
imperfections in the CSI. A robust non-diagonalizing code with
good minimum distance separation between received codewords is
proposed. The code is very suitable for systems with high data
rates due to its low design complexity. Numerical results show
that the proposed code outperforms a state of the art
diagonalizing precoder.
-
-
MIMO-ISI Channel equalization -- Which
Prize We Have to Pay for Causality
-
Holger Boche
(Heinrich-Hertz-Institut für Nachrichtentechnik Berlin GmbH,
Germany); Volker Pohl (Technical University Berlin, Germany)
In the
investigation of equalizers and precoders for multiple-input
multiple-output systems with intersymbol interference,
completely new phenomena appear if the causality of theses
filters is required. Both, the noise enhancement and the
robustness of the equalizing filter are important criteria which
influence the performance of the filter. It is shown that under
the causality constrain, the optimal filters with respect to
both criteria does not coincide such that a certain trade-off
between both performance measures has to be found. For precoders,
the effective receive power reduction is the most important
performance criteria. It is shown that the robustness of the
inverses and the effective receive power decreases exponential
with the number of transmit and receive antennas of the MIMO
system.
-
-
Switching effects of a virtual rotating
MIMO antenna
-
Robert Bains
(Norwegian Univ. of Science and Technology, Norway); Ralf Mueller
(Norwegian University of Science and Technology, Norway)
In a
previous paper a concept of compact MIMO-receiver was proposed
consisting of a single active receiver antenna and multiple
parasitic elements placed on a circle around the antenna. The
advantage of this MIMO-receiver is that the parasitic elements
can be placed much closer to the active receiver antenna than
half the carrier wavelength. The results in the previous paper
was mainly based on the concept of a continuously rotating
antenna, and didn't go into the details of the effects created
when the antenna rotates 360 degrees with discrete steps. In
another paper by the same authors the effects of a discrete
rotation were studied based on theoretical grounds. This paper
will study the effect of the discrete rotation and the switching
effects based on electromagnetic simulations.
-
-
Multi-user Topologies in Multi-Antenna
Wireless Networks
-
Christian
Peel (Brigham Young University, USA); Lee Swindlehurst (Brigham
Young University, USA); Wolfgang Utschick (Munich University of
Technology, Germany)
Recent
results on the throughput achievable with wireless networks have
not fully considered multiple antennas and multi-user links. We
introduce these topics by deriving the transport capacity of a
multiple-access channel with CSI available only at the receiver.
We also give the transport capacity of the multiple-access and
broadcast channels with full CSI. We use these topologies at the
physical layer of an ad-hoc network to obtain achievable
distance-weighted rate regions for a multi-antenna wireless
network. These regions are obtained by maximizing the
distance-weighted rate over all combinations of uplink and
downlink topologies, respectively. A Nash-equilibrium-seeking
algorithm is used to optimize the transmit covariance matrices
for the centralized topology search. Distributed algorithms for
topology creation are also presented which utilize only local
channel state information and compared with multi-user versions
of slotted ALOHA. Numerical examples show the benefit of uplink
topologies over point-to-point and downlink topologies,
especially at high transmit power, high numbers of antennas, and
a large number of nodes.
-
-
Randomized distributed Multi-antenna
Systems in Multi-path channels
-
Anna
Scaglione (Cornell University, USA); Birsen Sirkeci (Cornell
University, USA); Stefan Geirhofer (Cornell University, USA); Lang
Tong (Cornell University, USA)
A great
deal of research on MIMO systems is now trying to focus on
distributed designs to bring the advantages of co-located
antenna systems to nodes with a single RF front end, by
leveraging on the other nodes resources. Yet, most schemes that
are considered assume that the nodes encode their signals in a
fashion that requires at least the knowledge of the number of
nodes involved and in many cases the specific encoding rule to
use. Hence, while the hardware resources are distributed, the
protocols that are proposed are not. Recently we have proposed
schemes that are totally decentralized and using random matrix
theory we have studied the diversity attainable through these
schemes in flat fading channels. The goal of this paper is to
show that our general randomized designs are suitable to work in
frequency selective channels and can easily be adapted to block
space-time precoding schemes that are known to harvest diversity
not only from the multiple antennas but also from the multi-path.
14-II°): MIMO Transmission Techniques - 4
papers
Adua 2Wolfgang Utschick
(Munich University of Technology, Germany)
-
An Efficient Feedback Scheme with
Adaptive Bit Allocation for Dispersive MISO Systems
-
Leonid
Krasny (Ericsson Inc., USA); Dennis Hui (Ericsson Inc., USA)
In this
paper, we focus on a cellular system with M transmit antennas at
the base station (BTS) and one receive antenna at the mobile
(i.e. an M-input/single-output (MISO) channel), where the BTS
commands each mobile to transmit its channel state information
back to the BTS. Our main result is a specific feedback scheme
with adaptive bit allocation, where a binary tree-structured
vector quantizer is used to separately quantize different
channel taps at different level of quantization. We show that
proposed feedback scheme allows to exploit the different
statistics of the channel taps and results in a performance very
close (within 1dB) to the performance that can be obtained with
perfect channel knowledge at the BTS.
-
-
Generalized Receiver-Enhanced Cooperative
Spatial Multiplexing
-
Hilde
Skjevling (University of Oslo, Norway); David Gesbert (Eurecom
Institute, France); Are Hjřrungnes (Unversity of Oslo, Norway)
This paper
explores the idea of cooperative spatial multiplexing for use in
MIMO multi-cell networks. We imagine applying this cooperation
for several multiple antenna access-points to jointly transmit
streams towards multiple user terminals, with arbitrary number
of base station and user terminal antennas. We make the setting
more realistic by introducing a constraint on the {\em hybrid
channel state information} (HCSI), assuming that each
transmitter has full CSI for its own channel, but only {\em
statistical} information about other transmitters' channels.
Each cooperating transmitter then makes guesses about the
behaviour of the other transmitters, using the available
statistical CSI. We show two of several possible transmission
strategies under this setting, and include simple optimization
at the receiver to improve performance. Comparisons are made
with fully cooperative (full CSI) and non-cooperative schemes.
Simulation results show a substantial cooperation gain despite
the lack of instantaneous information.
-
-
Robust transmitter design in MISO
multiuser broadcast systems
-
Ami Wiesel (Technion-Israel
Institute of Technology, Israel)
We
consider the problem of transmitter design in multiuser
broadcast systems under channel uncertainty. In particular, we
are interested in broadcast systems in which the transmitter has
multiple antennas, and each user has a single receive antenna.
We assume that there are strict quality of service constraints
on the data rates of each of the users and try to minimize the
average transmitted power while maintaining these rates. This
problem was recently solved assuming perfect channel knowledge
at the transmitter, but is still an open question when only
partial channel state information (CSI) is available.
-
-
On MIMO Transmission Techniques for
Multiuser Communications
-
Wolfgang
Utschick (Munich University of Technology, Germany)
A
communication scenario with multiple cooperating transmitters,
which can perform a joint pre-processing of the signals to be
transmitted, and multiple decentralized receivers, which can
only process the received signals inde-pendently, is referred to
as (MIMO) Broadcast Channel. We consider receivers with a vector
receive signal, e.g., from multiple antenna elements. The
Broadcast Channel scenario occurs in wireline as well as in
wireless communi-cations (communication from access point to
multiple mobile terminals), which is considered here. In this
work we will critically review different optimality criteria and
algorithms for the design of MIMO transmission techniques under
the view of the amount of required channel state information
(CSI), computational complexity and performan-ce quality.
15-I°) MIMO Testbeds and Rapid Prototyping,
and Implementation Steps of MIMO Systems - 5 papers
Chairs: Markus
Rupp and Steffen Paul
AuditoriumSteffen Paul (Infineon
AG, Germany)
-
System Level Design Considerations for
HSUPA User Equipment
-
Moritz
Harteneck (Aeroflex Inc, United Kingdom)
Within
Release 6 of the 3GPP standards, one of the most important
features is High Speed Uplink Packet Access (HSUPA) or enhanced
DCH (E-DCH), which is the uplink counterpart for High Speed
Downlink Packet Access (HSDPA). Most notable improvements, when
compared to the R99 specification, are the achievable peak data
rate of 5.76 Mbps, reduced latency due to a shortened
transmission time interval and increased uplink cell throughput.
This has been achieved by the use of multi-code transmission on
the uplink, together with an improved forward error correction
scheme including the use of hybrid automatic repeat request
operating between the UE and the nodeB and a tighter (nodeB
based) control of the uplink resources. In this paper, system
level design considerations are de-rived which point out the
design problems one faces when designing a HSUPA compliant UE.
First, the HSUPA system is explained, then the receiver is
analysed in more detail and finally, considerations for the RF
transmitter block are shown.
-
-
IEEE 802.11n MIMO-Prototyping with Dirty
RF Using the Hardware-in-the-Loop Approach
-
Matthias
Stege (Signalion GmbH, Germany); Tim Hentschel (Signalion GmbH,
Germany); Michael Löhning (Signalion GmbH, Germany); Gerhard
Fettweis (Technische Universitaet Dresden, Germany); Marcus
Windisch (Technische Universität Dresden, Germany)
Modern
wireless systems employ highly integrated hardware. Especially
for the processing at radio frequencies this high integration
causes many undesired effects of signal distortion and
degradation that must be simulated comprehensively before
finalizing the system design. However, often the model accuracy
is not sufficient to obtain sound results of the simulations;
and in the case of sufficiently accurate models the simulation
times get immense. A way out is to use real radio frequency
hardware and digital physical layer simulations together in a
hardware-in-the-loop system. Short simulation times and
real-world radio characteristics are the unbeatable advantage of
the hardware-in-the-loop approach.
-
-
Real-Time Implementation of a Sphere
Decoder-Based MIMO Wireless System
-
Mikel
Mendicute (University of Mondragon, Spain); Luis Barbero
(University of Edinburgh, United Kingdom); Gorka Landaburu
(University of Mondragon, Spain); John. S Thompson (University of
Edinburgh, United Kingdom); Jon Altuna (University of Mondragon,
Spain); Vicente Atxa (University of Mondragon, Spain)
This
contribution analyzes the integration of the sphere decoder (SD)
in a complete field-programmable gate array (FPGA)-based
real-time multiple input-multiple output (MIMO) platform. The
algorithm achieves the performance of the maximum likelihood
detector (MLD) with reduced complexity. However, its
non-deterministic complexity, depending on the noise level and
the channel conditions, hinders its integration process. This
paper evaluates the performance and limitations of the SD in a
real-time environment where signal impairments, such as symbol
timing, imperfect channel estimation or quantization effects are
considered.
-
-
Real-Time Experiments on Channel Adaptive
Transmission in the Multi-User Up-link at very high Data Rates
using MIMO-OFDM
-
Thomas
Haustein (Heinrich Hertz Institut Berlin, Germany); Andreas Forck
(HHI, Germany); Holger Gäbler (FhG-HHI, Germany); Volker
Jungnickel (Fraunhofer Institut für Nachrichtentechnik (Heinrich-Hertz-Institut)
Berlin, Germany); Stefan Schiffermueller (FhG-HHI, Germany)
In this
paper we focus on channel adaptive transmission in the
multi-user OFDM uplink where the base station uses multiple
antennas. The additional degree of freedom in space requires
extra signal processing effort which becomes challenging
especially for a high data rate implementation in real-time. Our
MIMO-OFDM experimental system which is capable to transmit data
rates beyond 1~Gbit/s, was enhanced by adaptive resource
allocation, where the modulation on each antenna and each
sub-carrier was controlled by a narrow-band feed-back channel.
We present experimental results for the total rate achieved at
the base station and the individual rates per user terminal in
line-of-sight and non-line-of-sight scenarios. We compare the
rates expected from theory on the measured indoor channels with
rates achieved in the experiments.
-
-
An 8x8 RLS based MIMO detection ASIC for
broadband MIMO-OFDM wireless transmissions
-
Jingming
Wang (Marvell Semiconductor, USA); Babak Daneshrad (University of
California, Los Angeles, USA)
This paper
presents the architecture and VLSI implementation of a highly
flexible MIMO detection engine which supports a wide array of
configurations ranging from 1x1 to 8x8 square, as well as all
possible non-symmetric MIMO configurations. The chip is
specifically designed to work with an underlying OFDM modulation
scheme, and can cover the range of 64 to 1024 subchannels. The
chip implements an RLS based MIMO solution which provides a good
balance between hardware complexity and overall system
performance. To further reduce the complexity, frequency domain
linear interpolation is also used. The actual implementation is
based upon the highly scalable inverse QR decomposition based
systolic array architecture. A single systolic array is
time-multiplexed for all OFDM subchannels. This naturally
overcomes the pipelining difficulty in traditional single
channel systolic arrays without doubling the array size. In
conjunction with the array design, a unique input tagging scheme
is incorporated to allow dynamic reconfiguration of the ASIC on
a per packet basis, and also to reduce power consumption when
only a sub-array is needed for the operation. The final
implementation of the MIMO detection engine supports up to an
8x8 configuration in 12.5 MHz of bandwidth. A 4x4 or any smaller
array can also be supported at up to 25 MHz of bandwidth. The
chip was fabricated using a 3.3V/1.8V 0.18um CMOS technology.
The resulting core layout measures 29.2mm^2 and clocks at a
maximum clock frequency of 58MHz. The power consumption of the
chip in a 2x2-25 MHz configuration is 360 mW, whereas the 12.5
MHz 8x8 mode consumes 830mW.
15-II°) MIMO Testbeds and Rapid
Prototyping, and Implementation Steps of MIMO Systems - 5 papers
Chairs: Markus
Rupp and Steffen Paul
AuditoriumSteffen Paul (Infineon
AG, Germany)
-
Design of WARP: A Wireless Open-Access
Research Platform
-
Patrick
Murphy (Rice University, USA); Ashutosh Sabharwal (Rice
University, USA); Behnaam Aazhang (Rice University, USA)
This paper
presents the design of WARP, a custom platform for research in
advanced wireless algorithms and applications. The platform
consists of both custom hardware and FPGA implementations of key
communications blocks. The hardware consists of FPGA-based
processing boards coupled to wideband radios and other I/O
interfaces; the algorithm implementations already include a
flexible OFDM physical layer. Both the hardware design and
algorithm implementations will be freely available to academic
researchers to enable the development of a widely disseminated,
highly capable platform for wireless research.
-
-
High-throughput multi-rate LDPC decoder
based on architecture-oriented parity check matrices
-
Predrag
Radosavljevic (Rice University, USA); Alexandre de Baynast (Rice
University, USA); Marjan Karkooti (Rice University, USA); Joseph
Cavallaro (Rice University, USA)
High
throughput pipelined LDPC decoder that supports multiple code
rates and codeword sizes is proposed. In order to increase
memory throughput, irregular block structured parity-check
matrices are designed with the constraint of equally distributed
odd and even nonzero block-columns in each horizontal layer for
pre-determined set of code rates. Designed decoder achieves data
throughput of approximately 1 Gb/s without sacrificing
error-correcting performance of capacity-approaching irregular
block codes. The prototype architecture is implemented on FPGA.
-
-
Fast Prototyping of Digital Signal
Processing Systems by Means of a Mopdel-based Codesign Environment
-
Leonardo
Reyneri (Politecnico di Torino, Italy); Fabio Ancona (Sundance
Italia s.r.l., Italy)
This paper
presents a novel tool, based on Simulink, for model-based
high-level HW/SW codesign of high-performance digital signal
processing systems. The tool has been tailored to support HW/SW
configurable platforms, in particular those from Sundance
Microprocessor Technology
-
-
MIMO Signal Processing on a
reconfigurable architecture
-
Klaus Hueske
(University of Dortmund, Germany); Juergen Goetze (University of
Dortmund, Germany)
In this
paper the implementation of multiple-input multiple-output
(MIMO) signal processing on a reconfigurable hardware
architecture is discussed. The implementation of MIMO systems is
usually determined by the parameters of the application at hand,
e.g. the number of input signals, number of output signals,
number of users or word length. Furthermore, there is also a
flexibility in terms of the algorithms, which are used for
computing the required task. We will present the implementation
of the linearly constrained MVDR beamformer on a reconfigurable
hardware architecture. A virtual parallel implementation of the
used algorithms is mapped to a reconfigurable hardware
architecture, where the used processor elements can execute
different modes (configuration modes). We will discuss the
configuration in terms of change of parameters and change of
algorithm, respectively. Furthermore, bit true simulations of
the BER for different configurations are presented for various
word lengths. Finally, the trade-off between performance and
reconfiguration effort is discussed.
-
-
VLSI Implementation of Pipelined Sphere
Decoding with Early Termination
-
Andreas Burg
(ETHZ, Switzerland); Markus Wenk (IIS/ETH-Zurich, Switzerland);
Wolfgang Fichtner (ETHZ, Switzerland)
The sphere
decoding algorithm allows to implement MIMO detection with
maximum likelihood error rate performance while complexity is
far below an exhaustive search. This paper addresses two
important problems associated with the practical implementation
of sphere decoding: the mitigation of the bit error rate
performance loss when the runtime of the decoder is constrained
and the introduction of pipelining into the recursive
depth-first sphere decoding algorithm. The result of this work
is a sphere decoder implementation for a 4x4 system with 16-QAM
modulation in a 0.13 um technology that achieves a guaranteed
minimum throughput of 761 Mbps.
16) Advances in Monte Carlo methods for
target tracking - 7 papers
Chairs: Petar
Djuric and Monica Bugallo
Sala VerdePetar Djuric
(State University of New York at Stony Brook, USA)
-
Controlling particle filter
regularization for GPS/INS hybridization
-
Audrey
Giremus (university of Toulouse, France); Jean-Yves TOURNERET (IRIT/ENSEEIHT/TéSA,
France)
Coupling
GPS with Inertial Navigation Systems (INS) is an interesting way
of improving navigation performance in terms of accuracy and
continuity of service. This coupling is generally performed by
using GPS pseudorange measurements to estimate INS estimation
errors and sensor biases. Particle filtering techniques are good
candidates to solve the corresponding estimation problem due to
the nonlinear measurement equation. However, classical particle
filter algorithms tends to degenerate for this application
because of the small state noise. Regularized particle filters
allow to overcome this limitation at the expense of noisy state
estimates. A recent regularized particle filter was proposed to
control the regularization process by a Metropolis-Hasting step.
The method was shown to increase particle filter robustness
while decreasing the variance of the estimates. This paper goes
further by introducing an appropriate criterion which measures
the degeneracy of the particle cloud. This criterion is used to
control the regularization which is not applied systematically
reducing the algorithm computational cost. The main idea of the
proposed strategy is to monitor on line the mean jumps of the
predicted measurement likelihood by means of a CUSUM algorithm.
Simulation results are proposed to validate the relevance of the
criterion and the performance of the overall algorithm.
-
-
Efficient Variable Rate Particle Filters
For Tracking Manoeuvring Targets Using An MRF-based Motion Model
-
William Ng
(University of Cambridge, United Kingdom); Sze Kim Pang
(University of Cambridge, United Kingdom); Jack Li (University of
Cambridge, United Kingdom); Simon GODSILL (University of
Cambridge, United Kingdom)
In this
paper we describe an efficient real-time tracking algorithm for
multiple manoeuvring targets using particle filters. We combine
independent partition filters with a Markov Random Field motion
model to enable efficient and accurate tracking for interacting
targets. A Poisson model is also used to model both targets and
clutter measurements, avoiding the data association difficulties
associated with traditional tracking approaches. Moreover, we
present a variable rate dynamical model in which the states
change at different and unknown rates compared with the
observation process, thereby being able to model parsimoniously
the manoeuvring behaviour of an object even though only a single
dynamical model is employed. Computer simulations demonstrate
the potential of the proposed method for tracking multiple
highly manoeuvrable targets in a hostile environment with high
clutter density and low detection probability.
-
-
A Particle Filter for Beacon-Free Node
Location and Target Tracking in Sensor Networks
-
Joaquín
Míguez (Universidad Carlos III de Madrid, Spain); Antonio
Artés-Rodríguez (Universidad Carlos III de Madrid, Spain)
We address
the problem of tracking a maneuvering target that moves along a
region monitored by a sensor network, whose nodes, including
both the sensors and the data fusion center (DFC), are located
at unknown positions. Therefore, the node locations and the
target track must be estimated jointly without the aid of
beacons. We assume that, when the network is started, each
sensor is able to detect the presence of other nodes within its
range and transmit the resulting binary data to the DFC. After
this startup phase, the sensor nodes just measure some physical
magnitude related to the target position and/or velocity and
transmit it to the DFC. At the DFC, a particle filtering (PF)
algorithm is used to integrate all the collected data and
produce on-line estimates of both the (static) sensor locations
and the (dynamic) target trajectory. The validity of the method
is illustrated by computer simulations of a network of
power-aware sensors.
-
-
Tracking a Large Number of Targets in
Clutter with Particle Filter
-
Darko Musicki (University of
Melbourne, Australia); Mark Morelande (University of Melbourne,
Australia)
Multitarget tracking in clutter has two levels of complexity.
One is caused by the exponential increase of number of
measurement histories in time, and the other is caused by
complexity in allocating measurements to tracks in each scan,
which is also exponential in the number of tracks and the number
of measurements involved. Linear Multitarget tracking is a
Bayesian method for multi target tracking which dispenses with
measurement to track allocation completely. This results in
complexity which is linear in the number of tracks and the
number of measurements. This method is seamlessly integrated
with a number of filters which use the target existence paradigm.
In this paper the Linear Multitarget methodology is integrated
with a particle filter implementation of IPDA and applied to a
situation where a large number of targets with crossing
trajectories exist in significant clutter. A simulation study
shows the effectiveness of this approach, concentrating on the
false track discrimination and track retention capabilities of
this filter.
-
-
On Low-Power Analog Implementation of
Particle Filters for Target Tracking
-
Rajbabu
Velmurugan (Georgia Tech, USA); Shyam Subramanian (Georgia Tech,
USA); Volkan Cevher (University of Maryland, USA); David Abramson
(Monash University, Australia); Kofi Odame (Georgia Tech, USA);
Jordan Gray (Georgia Tech, USA); Haw-Jing Lo (Georgia Tech, USA);
James McClellan (Georgia Tech, USA); David Anderson (Georgia Tech,
USA)
We propose
a low-power, analog and mixed-mode, implementation of particle
filters. Low-power analog implementation of nonlinear functions
such as exponential and arctangent functions is done using
multiple-input translinear element (MITE) networks. These
nonlinear functions are used to calculate the probability
densities in the particle filter. A bearings-only tracking
problem is simulated to present the proposed low-power
implementation of the particle filter algorithm.
-
-
A Joint Radar-Acoustic Particle Filter
Tracker with Acoustic Propagation
-
Volkan
Cevher (University of Maryland, USA); Milind Borkar (Georgia
Institute of Technology, USA); James McClellan (Georgia Institute
of Technology, USA)
In this
paper, a novel particle filter tracker is presented for target
tracking using collocated radar and acoustic sensors. Real-time
tracking of the target's position and velocity in Cartesian
coordinates is performed using batches of range and
direction-of-arrival estimates. For robustness, the filter
aligns the radar and acoustic data streams to account for
acoustic propagation delays. The filter proposal function uses a
Gaussian approximation to the full tracking posterior for
improved efficiency. To incorporate the aligned acoustic data
into the tracker, a two-stage weighting strategy is proposed.
Computer simulations are provided to demonstrate the
effectiveness of the algorithm.
-
-
Advances in Cost-Reference Particle
Filtering
-
Monica
Bugallo (Stony Brook University, USA); Petar Djuric (State
University of New York at Stony Brook, USA)
Recently,
we have proposed a particle filtering-type methodology, which we
refer to as cost-reference particle filtering (CRPF). Its main
feature is that it is not based on any particular probabilistic
assumptions regarding the studied dynamic model. The concepts of
particles and particle streams, however, are the same in CRPF as
in standard particle filtering (SPF), but the probability masses
of the particles are replaced with user defined costs. In this
paper we propose some modifications of the original CRPF
methodology. The changes allow for development of simpler
algorithms, which may also be less computationally intensive and
possibly more robust. We investigate several variants of CRPF
and compare them with SPF. The advantages and disadvantages of
the considered algorithms are illustrated and discussed through
computer simulations of tracking of multiple targets which move
along a two-dimensional space.
17) Signal Processing in Radar Imaging - 7
papers
Chair: Victor
Chen and Marco Martorella
Room 4Victor Chen (US
Naval Research Laboratory, USA)Marco Martorella (University of Pisa,
Italy)
-
A slope-based technique for motion
estimation and optimum time selection for ISAR imaging of ship
targets
-
Debora
Pastina (University of Rome "La Sapienza", Italy); Chiara Spina (Selex
Airborne and Sensor Systems - Galileo Avionica Spa, Italy); Angelo
Aprile (Selex Airborne and Sensor Systems - Galileo Avionica Spa,
Italy)
The focus
of this paper is on optimum time selection and angular motion
estimation for ship ISAR imaging. The aim is to select proper
imaging intervals and to estimate ship angular motion in order
to obtain high quality top-view or side-view ship images
suitable for processing by classifica-tion/identification
procedures. To this purpose a slope-based ISAR algorithm is
proposed, able to estimate the time instants better suited for
top or side-view image formation and the rotation motion
vertical/horizontal components for image scaling. The
performance of the proposed ISAR tech-nique is investigated
against simulated data under different ship model, ship motion,
acquisition geometry and back-ground conditions. Results
obtained by applying the pro-posed technique to live ISAR data
proves the effectiveness of the proposed approach.
-
-
Radar Imaging via Adaptive MIMO
Techniques
-
Luzhou Xu
(University of Florida, USA); Jian Li (University of Florida,
USA); Petre Stoica (Uppsala University, Sweden)
We
investigate several adaptive techniques for a multiple-input
multiple-output (MIMO) radar system. By transmitting independent
waveforms via different antennas, the echoes due to targets at
different locations are linearly independent of each other,
which allows the direct application of many adaptive techniques.
We discuss several adaptive radar imaging algorithms, which can
provide excellent estimation accuracy of both target locations
and target amplitudes, and high robustness to the array
calibration errors. To reject the false peaks due to the strong
jammers, we also propose a generalized likelihood ratio test (GLRT).
As shown by the numerical examples, the number of targets can be
estimated accurately by using GLRT, and an accurate description
of the target scenario can be obtained by combining the adaptive
radar imaging algorithms and the GLRT technique.
-
-
Optimised Image Autofocusing for
Polarimetric ISAR
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Marco
Martorella (University of Pisa, Italy)
The use of
full polarisation enables multi-channel SAR processing for
enhancing both imaging and classification capabilities. In the
field of Inverse Synthetic Aperture Radar (ISAR) very little has
been investigated, especially from the point of view of
multi-channel ISAR image formation. In this paper, the authors
want to define an optimised image auto-focusing technique that
exploits full polarisation informa-tion. Theory and simulation
results will be provided in the paper.
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S-Method in radar imaging
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Ljubisa
STANKOVIC (University of Montenegro, Serbia and Montenegro);
Thayananthan Thayaparan (Radar Applications and Space Technology,
Defence Research and Development Canada, Ottawa, Canada, Canada);
Milos Dakovic (University of Montenegro, Serbia and Montenegro);
Vesna Popovic (University of Montenegro, Serbia and Montenegro)
Commonly
used technique for the SAR and ISAR signal analysis is a
two-dimensional Fourier transform. Moving targets in SAR or
maneuvering targets in ISAR case, induce Doppler-shift and
Doppler spread in the returned signal, producing blurred or
smeared images. Standard techniques for the solution of these
problems are motion compensation and time-frequency analysis
based techniques. Both of them are computationally intensive.
Here, we will present a numerically simple S-method based
approach that belongs to the time-frequency techniques. Beside
the basic S-method here we will present the signal adaptive form
and two-dimensional form of this method. They improve
readability of the radar images what will be demonstrated on the
simulated SAR and ISAR setups.
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AD-based Detector for Denoising in ISAR
Imaging
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Omar Yeste (Universidad
Politécnica de Madrid, Spain); Jesús Grajal (Universidad
Politécnica de Madrid, Spain)
We have
investigated two different strategies to improve the quality of
ISAR images corrupted by Gaussian noise. The images are
generated using a Time Frequency technique known as Atomic
Decomposition (AD). The first strategy is a classical denoising
technique based on an AD detector developed for signal detection
in noise. The second technique separates the atoms extracted
through AD by their parameters in two classes: atoms coming from
noise and atoms coming from signal components. Compared to the
first one, the second technique requires a greater knowledge
about the signal components.
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A Novel Focusing Technique for ISAR in
case of Uniform Rotation Rate
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José María Muńoz-Ferreras (Universidad
Politécnica de Madrid, Spain); Félix Pérez-Martínez (Universidad
Politécnica de Madrid, Spain)
A method
for the correction of Migration Through Resolution Cells (MTRC)
in ISAR (Inverse Synthetic Aperture Radar) is addressed here.
The new technique needs neither to know the target motion
parameters, to estimate them nor to use optimization to maximize
(minimize) an image focusing indicator. It assumes that the
target rotation rate is uniform and the direction of the
effective rotation vector does not change during the Coherent
Processing Interval (CPI). The algorithm corrects the MTRC in
two phases: Slant Range Rotation Compensation (SRRC) and Cross
Range Rotation Compensation (CRRC), where CRRC is based on an
extension of the Phase Difference method (PD). The effectiveness
of the proposed technique is verified with simulated (MIG-25
aircraft) and real (sailboat) radar data and compared with the
standard Range-Doppler Algorithm (RDA).
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Signal Processing for Target Motion
Estimation and Image Formation in Radar Imaging of Moving Targets
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Trygve Sparr
(FFI, Norway)
Radar
imaging of moving targets is often called ISAR (Inverse
Synthetic Aperture Radar.) Imaging of moving targets generally
consists of two separate tasks: Estimation and correction of
target motion, and the explicit image formation. Both tasks must
be implemented with great care, as it is the coherent processing
of the received radar signal phase that makes imaging possible.
Of the two tasks, the motion compensation is often most
difficult, as many radar targets move in a complicated and
fairly unpredictable manner. When the motion is complicated, the
imaging step can be a challenge as well. The reason is that the
target 3D-structure begins to matter, and projection plane
effects may cause blurred images for even well designed ISAR
processors.
18) Undetermined Sparse Audio Source
Separation - 4 papers
Chairs: Shoji
Makino and Shoko Araki
Adua 3Shoji Makino (NTT
Communication Science Laboratories, Japan)
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Sparse sources are separated sources
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Scott
Rickard (University College Dublin, Ireland)
Sparse
respresentations are being used to solve problems previously
thought insolvable. For example, we can separate more sources
than sensors using an appropriate transformation of the mixtures
into a domain where the sources are sparse. But what do we mean
by sparse? What attributes should a sparse measure have? And how
can we use this sparsity to separate sources? We investigate
these questions and, as a result, conclude that sparse sources
are separated sources, as long as you use the correct measure.
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Towards Underdetermined Source
Reconstruction from a Clasp-and-Play Binaural Live Recording
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Pau Bofill (Universitat
Politecnica de Catalunya, Spain)
The goal
of our current research is to be able to separate a few audio
sources from the signals of two microphones, using a separate
recording of each player clasping their hands. The separation is
performed in the frequency domain, where speech and music
signals are mostly sparse. The clasping is used to estimate each
transfer function, and the sources are reconstructed using
Second Order Cone Programming (SOCP). Our experiments show
moderatly good results for synthetic mixtures (11.5dB average
SNR) and poor results for the real case (2.2dB). This paper
points out some of the issues that make this task a difficult
one, and shows some experimental analysis of why this is so.
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Bayesian blind separation of audio
mixtures with structured priors
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Cédric
Févotte (University of Cambridge, United Kingdom)
In this
paper we describe a Bayesian approach for separation of linear
instantaneous mixtures of audio sources. Our method exploits the
sparsity of the source expansion coefficients on a
time-frequency basis, chosen here to be a MDCT. Conditionally
upon an indicator variable which is 0 or 1, one source
coefficient is either set to zero or given a Student t prior.
Structured priors can be considered for the indicator variables,
such as horizontal structures in the time-frequency plane, in
order to model temporal persistency. A Gibbs sampler (a standard
Markov chain Monte Carlo technique) is used to sample from the
posterior distribution of the indicator variables, the source
coefficients (corresponding to nonzero indicator variables), the
hyperparameters of the Student t priors, the mixing matrix and
the variance of the noise. We give results for separation of a
musical stereo mixture of 3 sources.
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Normalized Observation Vector Clustering
Approach for Sparse Source Separation
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Shoko Araki
(NTT communication Science Laboratories, Japan); Hiroshi Sawada (NTT
communication Science Laboratories, Japan); Ryo Mukai (NTT
communication Science Laboratories, Japan); Shoji Makino (NTT
Communication Science Laboratories, Japan)
This paper
presents a new method for the blind separation of sparse sources
whose number N can exceed the number of sensors M. Recently,
sparseness based blind separation has been actively studied.
However, most methods utilize a linear sensor array (or only two
sensors), and therefore have certain limitations; e.g., they
cannot be applied to symmetrically positioned sources. To allow
the use of more than two sensors that can be arranged in a
non-linear/non-uniform way, we propose a new method that
includes the normalization and clustering of the observation
vectors. We report promising results for the speech separation
of 3-dimensionally distributed five sources with non-linear/non-uniform
sensor arrangements of four sensors in a room (RT_{60}= 120 ms).
19) HW and SW architectures for multimedia
streaming Systems - 4+1 papers
Chairs: Luca
Fanucci and Fabrizio Rovati
Sala OniceLuca Fanucci
(University of Pisa, Italy)
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Current and future trends in embedded
VLIW microprocessors applied to multimedia and signal processing
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Giuseppe
Desoli (STMicroelectronics, Switzerland); Thierry Strudel (STMicroelectronics,
France); Jean-Philippe Cousin (STMicroelectronics, France);
Kaushik Saha (STMicroelectronics, India, India)
Although
Very Long Instruction Word (VLIW) processors mix of performance,
power consumption, flexibility and cost is a very good match for
embedded systems in general and multimedia streaming ones in
particular; they might be adversely exposed to increasing memory
latencies, code size bloat and to some extent performance
scalability with increasing issue width. This paper presents two
extensions for such VLIW micros that have a large potential
impact when applied to the highly competitive market of
multimedia con-sumer applications and more recently streaming:
Symmetric Multi Processor (SMP) cache coherency and
multithreading; we present a quick summary of those developments
carried out by STMicroelec-tronics within the framework of the
ST200 family of embedded mi-croprocessor and preliminary results
obtained from their use in selected video and audio applications
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Hardware co-processor for real-time and
high quality H.264/AVC video coding
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Maurizio
Martina (Politecnico di Torino, Italy); Guido Masera (Politecnico
di Torino, Italy); Luca Fanucci (University of Pisa, Italy);
Sergio Saponara (University of Pisa, Italy)
Real-Time
and High-Quality video coding is gaining a wide interest in the
research community, mainly for entertainment and leisure
applications. Furthemore H.264/AVC, the most recent standard for
high performance video coding, can be successfully exploited in
such a critical scenario. The need for high-quality imposes to
sustain up to tens of Mbits/s. To that purpose in this paper
optimized architectures for H.264/AVC most critical tasks,
Motion Estimation (ME) and Context Aware Binary Arithmetic
Coding (CABAC) are pro-posed. Post synthesis results on a 0.18
ľm standard cells technology show that the proposed
architectures can actu-ally process in real time 720x480 video
sequences at 30 Hz and grant more than 20Mbits/s in the simplest
configuration. Keywords: Video coding, H.264/AVC, Hardware
architec-tures, motion estimation, entropy coder
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Performance Optimization for Multimedia
Transmission in Wireless Home Networks
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Diego
Melpignano (STMicroelectronics, Italy); Gabriella Convertino (STMicroelectronics,
Italy); Andrea Vitali (STM, Italy); Juan Carlos De Martin
(Politecnico di Torino, Italy); Paolo Bucciol (Politecnico di
Torino, Italy); Antonio Servetti (Dipartimento di Automatica ed
Informatica - Politecnico di Torino, Italy)
This paper
describes a network adaptive real-time demonstrator for
converged applications (audio, video, voice, and data) on an
IEEE802.11g Wireless Home Network. Video transmission qual-ity
is optimised by dynamically adapting the source video bit-rate
to a real-time estimate of the available bandwidth on the
wireless network and by introducing data redundancy to recover
packet losses (Forward Error Correction). Video adaptation is
done by DCT-domain video transcoding algorithms performed in
real-time on a digital signal processor. Voice over Internet
Protocol (VoIP) services are offered manag-ing the coexistence
of 802.11g terminals and Bluetooth headsets. Audio time-scale
modification and adaptive playout algorithms enable robust and
high quality interactive voice communications minimizing the
effect of packet losses and jitter typical of wireless scenarios.
All devices can share and remotely control content via Universal
Plug and Play (UPnP).
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Design of Application Specific
Instruction-set Processor for Image and Video Filtering
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Sergio
Saponara (University of Pisa, Italy); Luca Fanucci (University of
Pisa, Italy); Stefano Marsi (University of Trieste, Italy);
Giovanni Ramponi (University of Trieste, Italy); Martin Witte
(University of Aachen, Germany); David Kammler (University of
Aachen, Germany)
Two
architectures for cost-effective and real-time implementation of
non-linear image and video filters are presented in the paper.
The first architecture is a traditional VHDL-based ASIC (Application
Specific Integrated Circuit) design while the second one is an
ADL (Architecture Description Language) based ASIP (Application
Specific Instruction Set Processor). A system to improve the
visual quality of images, based on Retinex-like algorithm, is
referred as case study. First, starting from a high-level
functional description the design space is explored to achieve a
linearized structural C model of the algorithm with finite
arithmetic precision. For the algorithm design space exploration
visual and complexity criteria are adopted while a statistical
analysis of typical input images drives the algorithm
optimization process. The algorithm is implemented both as ASIC
and ASIP solution in order to explore the trade-off between the
flexibility of a software solution and the power and complexity
optimization of a dedicated hardware design. The aim is to
achieve the desired algorithmic functionality and timing
specification at reasonable complexity and power costs. Taking
advantage of the processor programmability, the flexibility of
the system is increased, involving e.g. dynamic parameter
adjustment and color treatment. Gate level implementation
results in a 0.18ľm standard-cell CMOS technology are presented
for both the ASIC and ASIP approach
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An H.264-Based Video Encoding Scheme for
3D TV
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Mahsa T.
Pourazad (University of British Columbia, Canada); Panos
Nasiopoulos (University of British Columbia, Canada); Rabab Ward
(University of British Columbia, Canada)
This paper
presents an H.264-based scheme for compress-ing 3D content
captured by 3D depth range cameras. Exist-ing MPEG-2 based
schemes take advantage of the correla-tion between the 2D video
sequence and its corresponding depth map sequence, and use the
2D motion vectors (MV) for the depth video sequence as well.
This improves the speed of encoding the depth map sequence, but
it results in an increase in the bitrate or a drop in the
quality of the re-constructed 3D video. This is found to be due
to the MVs of the 2D video sequence not being the best choice
for encod-ing some parts of the depth map sequence containing
sharp edges or corresponding to distant objects. To solve this
problem, we propose an H.264-based method which re-estimates the
MVs and re-selects the appropriate modes for these regions.
Experimental results show that the proposed method enhances the
quality of the encoded depth map se-quence by an average of 1.77
dB. Finding the MVs of the sharp edge-included regions of the
depth map sequence amounts to 30.64% of the computational effort
needed to calculate MVs for the whole depth map sequence.
10)
NEWCOM - 6 papers
AuditoriumErdal
Panayirci (Bilkent University, Turkey)
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Code-aided Frequency Ambiguity Resolution
and Channel Estimation for MIMO OFDM systems
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Frederik
Simoens (Ghent University, Belgium); Marc Moeneclaey (Ghent
University, Belgium)
This
contribution deals with channel estimation and frequency
ambiguity resolution in a MIMO OFDM context. Existing blind
frequency-recovery algorithms for OFDM are able to provide a
reliable estimate of the frequency offset up to an integer
multiple of the subcarrier spacing. To resolve the remaining
ambiguity, one can employ either pilot symbols or the unknown
coded data symbols. Clearly, the latter method results in a
higher bandwidth efficiency. Similar considerations hold for the
estimation of a frequency-selective MIMO channel. In this
contribution, we propose a code-aided technique to jointly
estimate the channel and resolve the frequency ambiguity. The
estimator is based on the expectation-maximization (EM)
algorithm and exploits information from the unknown coded data
symbols and only a small number of pilot symbols. A significant
performance gain is observed compared to existing, solely
pilot-based estimation techniques.
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New Results in Iterative Frequency-Domain
Decision-Feedback Equalization
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Frédérique
Sainte-Agathe (Supélec, Thales Communication, France); Hikmet Sari
(Ecole Supérieure d'Electricité (SUPELEC), France)
Single-carrier transmission with frequency-domain equalization (SCT/FDE)
is today recognized as an attractive alternative to orthogonal
frequency-division multiplexing (OFDM) for wireless applications
with large channel dispersions. In this paper, we investigate
iterative frequency-domain decision- feedback equalization (FD/DFE),
which significantly improves performance compared to minimum
mean-square error (MMSE) and zero-forcing (ZF) linear equalizers.
We introduce a new FD/DFE and compare it to previously proposed
equalizers.
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Network Planning for Multi-radio
Cognitive Wireless Networks
-
Xiaodong
Wang (Columbia University, USA)
We propose
a general network planning framework for multi-radio
multi-channel cognitive wireless networks. Under this framework,
data routing, resource allocation, and scheduling are jointly
designed to maximize a network utility function. We treat such a
cross-layer design problem with fixed radio distributions across
the nodes and formulate it as a large-scale convex optimization
problem. A primal-dual method together with the
column-generation technique is proposed to efficiently solve
this problem. Simulation studies are carried out to assess the
performance of the proposed cross-layer network planning
framework. It is seen that the proposed approach can
significantly enhance the overall network performance.
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Space-Time Block Coding for Noncoherently
Detected CPFSK
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Fabrizio
Pancaldi (University of Modena - Dept. of Information Eng., Italy);
Giorgio M. Vitetta (University of Modena and Reggio Emilia, Italy)
In this
paper the problem of unitary rate space-time block coding for
multiple-input multiple-output communication systems employing
continuous phase frequency shift keying is investigated. First,
the problem of optimal codeword by codeword noncoherent
detection is analysed; then, design criteria for optimal
space-time clock codes are proposed and some novel coding
schemes are devised. Simulation results evidence that the
proposed schemes can efficiently exploit spatial diversity and
that their use can entail a limited energy loss with respect to
other solutions available in the technical literature for
coherent systems, with the substantial advantage, however, of a
simple detection algorithm.
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