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Adaptive minimum error-rate filtering design: a review

Adaptive minimum error-rate filtering design: a review
Adaptive minimum error-rate filtering design: a review
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.
0165-1684
1671-1697
Chen, S.
ac405529-3375-471a-8257-bda5c0d10e53
Tan, S.
6ee9d7e3-0cd0-41b9-805e-9c4edba790b6
Xu, L.
5802ae7f-4a22-4308-a6d8-8d8ae171553d
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1
Chen, S.
ac405529-3375-471a-8257-bda5c0d10e53
Tan, S.
6ee9d7e3-0cd0-41b9-805e-9c4edba790b6
Xu, L.
5802ae7f-4a22-4308-a6d8-8d8ae171553d
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1

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

Record type: Article

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.

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Published date: July 2008
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 265386
URI: https://eprints.soton.ac.uk/id/eprint/265386
ISSN: 0165-1684
PURE UUID: a9afef61-391d-41c9-9c8f-ff05803c3e95
ORCID for L. Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

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Date deposited: 02 Apr 2008 08:52
Last modified: 20 Jul 2019 01:26

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Contributors

Author: S. Chen
Author: S. Tan
Author: L. Xu
Author: L. Hanzo ORCID iD

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