Genetic Algorithm Assisted Error Probability Optimisation for Beamforming
Genetic Algorithm Assisted Error Probability Optimisation for Beamforming
A novel Genetic Algorithm (GA) assisted direct error probability optimisation technique is proposed for adaptive beamforming, which reduces the achievable error probability by nearly two orders of magnitude at a signal-to-noise ratio of 10dB in the investigated scenario in comparison to the minimum mean-squared error beamforming benchmarker.
320-322
Wolfgang, A.
e87811dd-7028-4ac3-90cc-62003ff22202
Ahmad, N.N.
f6105bf9-7a9b-4e91-b1fa-4372662de087
Chen, S.
9310a111-f79a-48b8-98c7-383ca93cbb80
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1
4 March 2004
Wolfgang, A.
e87811dd-7028-4ac3-90cc-62003ff22202
Ahmad, N.N.
f6105bf9-7a9b-4e91-b1fa-4372662de087
Chen, S.
9310a111-f79a-48b8-98c7-383ca93cbb80
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1
Wolfgang, A., Ahmad, N.N., Chen, S. and Hanzo, L.
(2004)
Genetic Algorithm Assisted Error Probability Optimisation for Beamforming.
Electronics Letters, 40 (5), .
Abstract
A novel Genetic Algorithm (GA) assisted direct error probability optimisation technique is proposed for adaptive beamforming, which reduces the achievable error probability by nearly two orders of magnitude at a signal-to-noise ratio of 10dB in the investigated scenario in comparison to the minimum mean-squared error beamforming benchmarker.
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el_ga_mber_beam.ps
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Text
aw-nna-sqc-lh-march04-ee.pdf
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More information
Published date: 4 March 2004
Organisations:
Southampton Wireless Group
Identifiers
Local EPrints ID: 259061
URI: http://eprints.soton.ac.uk/id/eprint/259061
ISSN: 0013-5194
PURE UUID: b86ab96a-1700-48fd-a44f-6710b5820708
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Date deposited: 11 Mar 2004
Last modified: 18 Mar 2024 02:33
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Contributors
Author:
A. Wolfgang
Author:
N.N. Ahmad
Author:
S. Chen
Author:
L. Hanzo
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