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Symmetric Kernel Detector for Multiple-Antenna Aided Beamforming Systems

Symmetric Kernel Detector for Multiple-Antenna Aided Beamforming Systems
Symmetric Kernel Detector for Multiple-Antenna Aided Beamforming Systems
We propose a powerful symmetric kernel classifier for nonlinear detection in challenging rank-deficient multipleantenna aided communication systems. By exploiting the inherent odd symmetry of the optimal Bayesian detector, the proposed symmetric kernel classifier is capable of approaching the optimal classification performance using noisy training data. The classifier construction process is robust to the choice of the kernel width and is computationally efficient. The proposed solution is capable of providing a signal-to-noise ratio gain in excess of 8 dB against the powerfull linear minimum bit error rate benchmarker, when supporting five users with the aid of three receive antennas.
2486-2491
Chen, S.
ac405529-3375-471a-8257-bda5c0d10e53
Wolfgang, A.
e87811dd-7028-4ac3-90cc-62003ff22202
Harris, C.J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1
Chen, S.
ac405529-3375-471a-8257-bda5c0d10e53
Wolfgang, A.
e87811dd-7028-4ac3-90cc-62003ff22202
Harris, C.J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1

Chen, S., Wolfgang, A., Harris, C.J. and Hanzo, L. (2007) Symmetric Kernel Detector for Multiple-Antenna Aided Beamforming Systems. 2007 International Joint Conference on Neural Networks, United States. 12 - 17 Aug 2007. pp. 2486-2491 .

Record type: Conference or Workshop Item (Other)

Abstract

We propose a powerful symmetric kernel classifier for nonlinear detection in challenging rank-deficient multipleantenna aided communication systems. By exploiting the inherent odd symmetry of the optimal Bayesian detector, the proposed symmetric kernel classifier is capable of approaching the optimal classification performance using noisy training data. The classifier construction process is robust to the choice of the kernel width and is computationally efficient. The proposed solution is capable of providing a signal-to-noise ratio gain in excess of 8 dB against the powerfull linear minimum bit error rate benchmarker, when supporting five users with the aid of three receive antennas.

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More information

Published date: 2007
Additional Information: Event Dates: 12- 17 August 2007
Venue - Dates: 2007 International Joint Conference on Neural Networks, United States, 2007-08-12 - 2007-08-17
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 264420
URI: http://eprints.soton.ac.uk/id/eprint/264420
PURE UUID: 58a081bb-5878-47a9-82e0-b5fd5b14f364
ORCID for L. Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 20 Aug 2007
Last modified: 03 Dec 2019 02:06

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Contributors

Author: S. Chen
Author: A. Wolfgang
Author: C.J. Harris
Author: L. Hanzo ORCID iD

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