Low-complexity equalization based on least squares support vector classifiers for DS-UWB systems

Authors:
Mohamed Musbah;Xu Zhu
Affiliations:
Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool, UK;Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool, UK
Venue:
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Year:
2009

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Abstract

We propose the least squares support vector classifier (LS-SVC) based equalization schemes for direct sequence ultra wideband (DS-UWB) systems, where a bank of independent LS-SVCs are employed to detect each block of signals. The LS-SVC based equalizers provide a close bit error rate (BER) performance in the line-of-sight (LOS) scenario to the case with additive white Gaussian noise (AWGN). Simulation results show that the LS-SVC based equalizers have almost identical BER performance to that of typical support vector classifiers (SVCs) with a reduced training complexity. Furthermore, the sparse LSSVCs are employed to reduce the detection complexity, with little performance loss compared to LS-SVCs.