Blind channel identification based on higher-order cumulant fitting using genetic algorithms
Blind channel identification based on higher-order cumulant fitting using genetic algorithms
A family of blind equalisation algorithms identifies a channel model based on a higher-order cumulant (HOC) fitting approach. Since HOC cost functions are multimodal, gradient search techniques require a good initial estimate to avoid converging to local minima. We present a blind identification scheme which uses genetic algorithms (GAS) to optimise a HOC cost function. Because GAS are efficient global optimal search strategies, the proposed method guarantees to find a global optimal channel estimate. A micro- GA implementation is adopted to further enhance computational efficiency. As is demonstrated in computer simulation, this GA based scheme is robust and accurate, and has a fast convergence performance.
184-188
Chen, S.
9310a111-f79a-48b8-98c7-383ca93cbb80
Wu, Y.
84854e37-ada6-4cc8-995f-6ce5ebc77423
McLaughlin, S.
d8651585-025f-4ea9-bd15-cef87f323624
1997
Chen, S.
9310a111-f79a-48b8-98c7-383ca93cbb80
Wu, Y.
84854e37-ada6-4cc8-995f-6ce5ebc77423
McLaughlin, S.
d8651585-025f-4ea9-bd15-cef87f323624
Chen, S., Wu, Y. and McLaughlin, S.
(1997)
Blind channel identification based on higher-order cumulant fitting using genetic algorithms.
Proceedings of 5th IEEE Signal Processing Workshop on Higher-Order Statistics.
.
Record type:
Conference or Workshop Item
(Other)
Abstract
A family of blind equalisation algorithms identifies a channel model based on a higher-order cumulant (HOC) fitting approach. Since HOC cost functions are multimodal, gradient search techniques require a good initial estimate to avoid converging to local minima. We present a blind identification scheme which uses genetic algorithms (GAS) to optimise a HOC cost function. Because GAS are efficient global optimal search strategies, the proposed method guarantees to find a global optimal channel estimate. A micro- GA implementation is adopted to further enhance computational efficiency. As is demonstrated in computer simulation, this GA based scheme is robust and accurate, and has a fast convergence performance.
Text
c-1997-spwhos
- Author's Original
More information
Published date: 1997
Additional Information:
5th IEEE Signal Processing Workshop on Higher-Order Statistics (Banff, Alberta, Canada), July 21-23, 1997 Organisation: IEEE Signal Processing Society
Venue - Dates:
Proceedings of 5th IEEE Signal Processing Workshop on Higher-Order Statistics, 1997-01-01
Organisations:
Southampton Wireless Group
Identifiers
Local EPrints ID: 251017
URI: http://eprints.soton.ac.uk/id/eprint/251017
PURE UUID: 04ac2acc-0b1b-41db-9b7d-b861ac4cdbb8
Catalogue record
Date deposited: 31 Mar 2000
Last modified: 14 Mar 2024 05:07
Export record
Contributors
Author:
S. Chen
Author:
Y. Wu
Author:
S. McLaughlin
Download statistics
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