Symmetric complex-valued RBF receiver for multiple-antenna aided wireless systems
Symmetric complex-valued RBF receiver for multiple-antenna aided wireless systems
A nonlinear beamforming assisted detector is proposed for multiple-antenna-aided wireless systems employing complex-valued quadrature phase shift-keying modulation. By exploiting the inherent symmetry of the optimal Bayesian detection solution, a novel complex-valued symmetric radial basis function (SRBF)-network-based detector is developed, which is capable of approaching the optimal Bayesian performance using channel-impaired training data. In the uplink case, adaptive nonlinear beamforming can be efficiently implemented by estimating the system’s channel matrix based on the least squares channel estimate. Adaptive implementation of nonlinear beamforming in the downlink case by contrast is much more challenging, and we adopt a cluster-variation-enhanced clustering algorithm to directly identify the SRBF center vectors required for realizing the optimal Bayesian detector. A simulation example is included to demonstrate the achievable performance improvement by the proposed adaptive nonlinear beamforming solution over the theoretical linear minimum bit error rate beamforming benchmark.
1657-1663
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1
Tan, S.
6ee9d7e3-0cd0-41b9-805e-9c4edba790b6
4 September 2008
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1
Tan, S.
6ee9d7e3-0cd0-41b9-805e-9c4edba790b6
Chen, Sheng, Hanzo, L. and Tan, S.
(2008)
Symmetric complex-valued RBF receiver for multiple-antenna aided wireless systems.
IEEE Transactions on Neural Networks, 19 (9), .
Abstract
A nonlinear beamforming assisted detector is proposed for multiple-antenna-aided wireless systems employing complex-valued quadrature phase shift-keying modulation. By exploiting the inherent symmetry of the optimal Bayesian detection solution, a novel complex-valued symmetric radial basis function (SRBF)-network-based detector is developed, which is capable of approaching the optimal Bayesian performance using channel-impaired training data. In the uplink case, adaptive nonlinear beamforming can be efficiently implemented by estimating the system’s channel matrix based on the least squares channel estimate. Adaptive implementation of nonlinear beamforming in the downlink case by contrast is much more challenging, and we adopt a cluster-variation-enhanced clustering algorithm to directly identify the SRBF center vectors required for realizing the optimal Bayesian detector. A simulation example is included to demonstrate the achievable performance improvement by the proposed adaptive nonlinear beamforming solution over the theoretical linear minimum bit error rate beamforming benchmark.
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Published date: 4 September 2008
Organisations:
Southampton Wireless Group
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Local EPrints ID: 266695
URI: http://eprints.soton.ac.uk/id/eprint/266695
PURE UUID: ee46c8f1-a344-4c82-8c34-50ea6075c940
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Date deposited: 23 Sep 2008 08:37
Last modified: 18 Mar 2024 02:34
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Author:
Sheng Chen
Author:
L. Hanzo
Author:
S. Tan
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