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Adaptive Bayesian decision feedback equaliser incorporating co-channel interference compensation

Adaptive Bayesian decision feedback equaliser incorporating co-channel interference compensation
Adaptive Bayesian decision feedback equaliser incorporating co-channel interference compensation
The paper derives a Bayesian decision feedback equaliser (DFE) which incorporates co-channel interfere (CCI) compensation. By exploiting the structure of CCI signals, the proposed Bayesian DFE can distinguish an interfering signal from white noise and uses this information to improve
performance. Adaptive implementation of this Bayesian DFE includes first using the standard least mean square (LMS) algorithm to identify the channel model and then estimating the co-channel states by means of a simple unsupervised clustering algorithm. Simulation involving a binary signal constellation is used to compare both the theoretical and adaptive performance of this Bayesian DFE with those of the maximum likelihood sequence estimator (MLSE). The results obtained indicate that, by compensating CCI, the Bayesian DFE can outperform the MLSE for the CCI.
530-533
Chen, S.
9310a111-f79a-48b8-98c7-383ca93cbb80
McLaughlin, S.
d8651585-025f-4ea9-bd15-cef87f323624
Mulgrew, B.
95a3fbda-7de2-4583-b1f2-0a54a69b414a
Grant, P. M.
e527fff4-da0f-4bc4-91cf-eed522070300
Chen, S.
9310a111-f79a-48b8-98c7-383ca93cbb80
McLaughlin, S.
d8651585-025f-4ea9-bd15-cef87f323624
Mulgrew, B.
95a3fbda-7de2-4583-b1f2-0a54a69b414a
Grant, P. M.
e527fff4-da0f-4bc4-91cf-eed522070300

Chen, S., McLaughlin, S., Mulgrew, B. and Grant, P. M. (1994) Adaptive Bayesian decision feedback equaliser incorporating co-channel interference compensation. Proceedings of IEEE International Conference on Communications. pp. 530-533 .

Record type: Conference or Workshop Item (Other)

Abstract

The paper derives a Bayesian decision feedback equaliser (DFE) which incorporates co-channel interfere (CCI) compensation. By exploiting the structure of CCI signals, the proposed Bayesian DFE can distinguish an interfering signal from white noise and uses this information to improve
performance. Adaptive implementation of this Bayesian DFE includes first using the standard least mean square (LMS) algorithm to identify the channel model and then estimating the co-channel states by means of a simple unsupervised clustering algorithm. Simulation involving a binary signal constellation is used to compare both the theoretical and adaptive performance of this Bayesian DFE with those of the maximum likelihood sequence estimator (MLSE). The results obtained indicate that, by compensating CCI, the Bayesian DFE can outperform the MLSE for the CCI.

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More information

Published date: 1994
Additional Information: IEEE International Conference on Communications (New Orleans, USA), May 1-5, 1994. Organisation: IEEE Communications Society
Venue - Dates: Proceedings of IEEE International Conference on Communications, 1994-01-01
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 251096
URI: http://eprints.soton.ac.uk/id/eprint/251096
PURE UUID: 7001735c-2253-4fad-af8d-5210d56d84da

Catalogue record

Date deposited: 13 Sep 2000
Last modified: 03 Feb 2022 17:49

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Contributors

Author: S. Chen
Author: S. McLaughlin
Author: B. Mulgrew
Author: P. M. Grant

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