A Robust Nonlinear Beamforming Assisted Receiver for BPSK Signalling
A Robust Nonlinear Beamforming Assisted Receiver for BPSK Signalling
Nonlinear beamforming designed for wireless communications is investigated. We derive the optimal nonlinear beamforming assisted receiver designed for binary phase shift keying (BPSK) signalling. It is shown that this optimal Bayesian beamformer significantly outperforms the classic linear minimum mean square error (LMMSE) beamformer at the expense of an increased complexity. Hence the achievable user capacity of the wireless system invoking the proposed beamformer is substantially enhanced. In particular, when the angular separation between the desired and interfering signals is below a certain threshold, a linear beamformer will fail while a nonlinear beamformer can still perform adequately. Blockadaptive implementation of the optimal Bayesian beamformer can be realized using a Radial Basis Function network based on the Relevance Vector Machine (RVM) for classification, and a recursive sample-by-sample adaptation is proposed based on an enhanced ?-means clustering aided recursive least squares algorithm.
1921-1925
Chen, S.
9310a111-f79a-48b8-98c7-383ca93cbb80
Wolfgang, A.
e87811dd-7028-4ac3-90cc-62003ff22202
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1
2005
Chen, S.
9310a111-f79a-48b8-98c7-383ca93cbb80
Wolfgang, A.
e87811dd-7028-4ac3-90cc-62003ff22202
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1
Chen, S., Wolfgang, A. and Hanzo, L.
(2005)
A Robust Nonlinear Beamforming Assisted Receiver for BPSK Signalling.
IEEE VTC'05 (Fall), Intercontinental Hotel, Dallas, United States.
25 - 28 Sep 2005.
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
Nonlinear beamforming designed for wireless communications is investigated. We derive the optimal nonlinear beamforming assisted receiver designed for binary phase shift keying (BPSK) signalling. It is shown that this optimal Bayesian beamformer significantly outperforms the classic linear minimum mean square error (LMMSE) beamformer at the expense of an increased complexity. Hence the achievable user capacity of the wireless system invoking the proposed beamformer is substantially enhanced. In particular, when the angular separation between the desired and interfering signals is below a certain threshold, a linear beamformer will fail while a nonlinear beamformer can still perform adequately. Blockadaptive implementation of the optimal Bayesian beamformer can be realized using a Radial Basis Function network based on the Relevance Vector Machine (RVM) for classification, and a recursive sample-by-sample adaptation is proposed based on an enhanced ?-means clustering aided recursive least squares algorithm.
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Published date: 2005
Additional Information:
Event Dates: 25-28 September 2005
Venue - Dates:
IEEE VTC'05 (Fall), Intercontinental Hotel, Dallas, United States, 2005-09-25 - 2005-09-28
Organisations:
Southampton Wireless Group
Identifiers
Local EPrints ID: 261798
URI: http://eprints.soton.ac.uk/id/eprint/261798
PURE UUID: f90c4f95-6f34-4ccd-8d1f-93d9db508af9
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Date deposited: 22 Jan 2006
Last modified: 18 Mar 2024 02:33
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Contributors
Author:
S. Chen
Author:
A. Wolfgang
Author:
L. Hanzo
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