A SYMBOL BY SYMBOL CLUSTERING BASED BLIND EQUALIZER (TueAmOR1)

Author(s) : Kristina Georgoulakis (University of Athens, Dept. of Informatics and Telecommunications, Greece)

Abstract : A new blind symbol by symbol equalizer is proposed. The operation of the proposed equalizer is based on the geometric properties of the two dimensional data constellation. An unsupervised clustering technique is used to locate the clusters formed by the received data. The symmetric properties of the clusters labels are subsequently investigated in order to label the clusters. Following this step, the received data are compared to clusters and decisions are made on a symbol by symbol basis by assigning to each data the label of the nearest cluster. The performance of the proposed equalizer is better compared to the performance of a CMA-based blind equalizer.

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