Stochastic gradient algorithms for equalisation in α-stable noise

Authors:
V. Bhatia;B. Mulgrew;A. T. Georgiadis
Affiliations:
Signals and Systems Group, IDCOM, School of Engineering and Electronics, The University of Edinburgh, Edinburgh, UK;Signals and Systems Group, IDCOM, School of Engineering and Electronics, The University of Edinburgh, Edinburgh, UK;Signals and Systems Group, IDCOM, School of Engineering and Electronics, The University of Edinburgh, Edinburgh, UK
Venue:
Signal Processing
Year:
2006

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Abstract

This paper addresses the problem of developing a least mean squares (LMS) style decision feedback equaliser algorithm for minimising bit error rate (BER) in impulsive noise environments characterised by the α-stable distribution. The development exploits the stable nature of the α-distribution and the concepts built on an earlier work in a Gaussian noise environment. Further, a Wiener-filter-with-limiter solution is also presented and used as a performance bench mark. An improvement in convergence and BER performance is achieved by using a minimum bit error rate (MBER) cost function instead of a conventional LMS-based design. The ability of least BER (LBER) equalisers based on a Gaussian noise assumption to operate in an α-stable noise environment is also highlighted.