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Paper data
Sequential Monte Carlo for Mobility Management in Wireless Cellular Networks

Yang Zigang, department of Electrical Engineering, Texas A&M University
Wang Xiaodong, department of Electrical Engineering, Columbia University, New York

Page numbers in the proceedings:
Volume II pp 181-184

Applications of Particle Filtering in Communications (1/2)

Paper abstract
We consider the application of sequential Monte Carlo (SMC) methodology to the problem of joint mobility tracking and soft handoff detection in cellular wireless communication networks based on the pilot signal strength measurements. The dynamics of the system under consideration are described by a nonlinear state-space model. Mobility tracking involves an on-line estimation of the location and velocity of the mobile, whereas handoff detection involves an on-line prediction of the pilot signal strength at future time instant. The optimal solution to both problems is prohibitively complex due to the nonlinear nature of the system. The sequential Monte Carlo (SMC) methods are therefore employed to track the probabilistic dynamics of the system and to make the corresponding estimates and predictions.

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