Adaptive minimum error-rate filtering design: a review


Chen, S., Tan, S., Xu, L. and Hanzo, L. (2008) Adaptive minimum error-rate filtering design: a review. Signal Processing, 88, (7), 1671-1697.

Download

[img] PDF (manuscript)
Available under License Creative Commons Attribution Share Alike.

Download (2054Kb)

Description/Abstract

Adaptive filtering has been an enabling technology and has found ever-increasing applications in various state-of-the-art communication systems. Traditionally, adaptive filtering has been developed based on the Wiener or minimum mean square error (MMSE) approach, and the famous least mean square algorithm with its low computational complexity readily meets the fast real-time computational constraint of modern high-speed communication systems. For a communication system, however, it is the system’s bit error rate (BER), not the mean square error (MSE), that really matters. It has been recognised that minimising the MSE criterion does not necessarily produce the minimum BER (MBER) performance. The introduction of the novel MBER design has opened up a whole new chapter in the optimisation of communication systems, and its design trade-offs have to be documented in contrast to those of the classic but actually still unexhausted MMSE and other often-used optimisation criteria. This contribution continues this theme, and we provide a generic framework for adaptive minimum error-probability filter design suitable for the employment in a variety of communication systems. Advantages and disadvantages of the adaptive minimum error-probability filter design are analysed extensively, in comparison with the classic Wiener filter design. Keywords: Adaptive filter; Wiener solution; Minimum mean square error; Minimum bit error rate; Stochastic gradient algorithm; Least mean square algorithm; Least bit error rate algorithm.

Item Type: Article
ISSNs: 0165-1684
Divisions: Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Comms, Signal Processing & Control
ePrint ID: 265386
Date Deposited: 02 Apr 2008 08:52
Last Modified: 27 Mar 2014 20:10
Further Information:Google Scholar
ISI Citation Count:5
URI: http://eprints.soton.ac.uk/id/eprint/265386

Actions (login required)

View Item View Item

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics