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Genetic algorithm optimization for maximum likelihood joint channel and data estimation

Genetic algorithm optimization for maximum likelihood joint channel and data estimation
Genetic algorithm optimization for maximum likelihood joint channel and data estimation
A novel blind equalisation scheme is developed based on maximum likelihood (ML) joint channel and data estimation. In this scheme, the joint ML optimisation is decomposed into a two-level optimisation loop. An efficient version of genetic algorithms (GAS), known as a micro GA, is employed at the upper level to identify the unknown channel model and the Viterbi algorithm (VA) is used at the lower level to provide the maximum likelihood sequence estimation of the transmitted data sequence. The proposed GA based scheme is accurate and robust, and has a fast convergence rate, as is demonstrated in simulation.
1157-1160
Chen, S.
9310a111-f79a-48b8-98c7-383ca93cbb80
Wu, Y.
84854e37-ada6-4cc8-995f-6ce5ebc77423
Chen, S.
9310a111-f79a-48b8-98c7-383ca93cbb80
Wu, Y.
84854e37-ada6-4cc8-995f-6ce5ebc77423

Chen, S. and Wu, Y. (1998) Genetic algorithm optimization for maximum likelihood joint channel and data estimation. Proceedings of 1998 IEEE International Conference on Acoustics, Speech and Signal Processing. pp. 1157-1160 .

Record type: Conference or Workshop Item (Other)

Abstract

A novel blind equalisation scheme is developed based on maximum likelihood (ML) joint channel and data estimation. In this scheme, the joint ML optimisation is decomposed into a two-level optimisation loop. An efficient version of genetic algorithms (GAS), known as a micro GA, is employed at the upper level to identify the unknown channel model and the Viterbi algorithm (VA) is used at the lower level to provide the maximum likelihood sequence estimation of the transmitted data sequence. The proposed GA based scheme is accurate and robust, and has a fast convergence rate, as is demonstrated in simulation.

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c-1998-icassp - Author's Original
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More information

Published date: 1998
Additional Information: IEEE International Conference on Acoustics, Speech and Signal Processing (Seattle, USA), May 12-15, 1998 Organisation: IEEE
Venue - Dates: Proceedings of 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, 1998-01-01
Organisations: Southampton Wireless Group

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Local EPrints ID: 251031
URI: http://eprints.soton.ac.uk/id/eprint/251031
PURE UUID: 2cdd8653-c3a5-4479-9f16-37943a942678

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Date deposited: 31 Mar 2000
Last modified: 14 Mar 2024 05:07

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Contributors

Author: S. Chen
Author: Y. Wu

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