DocumentCode :
1328983
Title :
Bayesian decision feedback equaliser for overcoming co-channel interference
Author :
Chen, S. ; McLaughlin, S. ; Mulgrew, B. ; Grant, RM
Author_Institution :
Dept. of Electr. & Electron. Eng., Portsmouth Univ., UK
Volume :
143
Issue :
4
fYear :
1996
fDate :
8/1/1996 12:00:00 AM
Firstpage :
219
Lastpage :
225
Abstract :
The authors derive a Bayesian decision feedback equaliser which incorporates co-channel interference compensation. By exploiting the structure of co-channel interfering signals, the proposed Bayesian decision feedback equaliser is able to distinguish an interfering signal from white noise and utilises this information to improve performance. Adaptive implementation of this Bayesian decision feedback equaliser includes identifying the channel model using the least mean square algorithm and estimating the co-channel states by means of an unsupervised clustering scheme. Simulation involving a binary signal constellation is used to compare both the theoretical and adaptive performance of this Bayesian decision feedback equaliser with those of the maximum likelihood sequence estimator. The results obtained indicate that, in the presence of severe co-channel interference, the Bayesian decision feedback equaliser employing the proposed simple scheme to compensate co-channel interference can outperform maximum likelihood sequence estimator that only treats co-channel interference as an additional coloured noise
Keywords :
Bayes methods; adaptive equalisers; cochannel interference; compensation; decision feedback equalisers; interference suppression; least mean squares methods; pattern recognition; state estimation; white noise; Bayesian decision feedback equaliser; adaptive implementation; binary signal constellation; channel model; co-channel interference; interference compensation; interfering signal; least mean square algorithm; performance; state estimation; unsupervised clustering; white noise;
fLanguage :
English
Journal_Title :
Communications, IEE Proceedings-
Publisher :
iet
ISSN :
1350-2425
Type :
jour
DOI :
10.1049/ip-com:19960612
Filename :
533171
Link To Document :
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