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Adaptive Minimum Bit Error Rate Beamforming

Adaptive Minimum Bit Error Rate Beamforming
Adaptive Minimum Bit Error Rate Beamforming
An adaptive beamforming technique is proposed based on directly minimizing the bit error rate. It is demonstrated that this minimum bit error rate (MBER) approach utilizes the antenna array elements more intelligently, than the standard minimum mean square error (MMSE) approach. Consequently, MBER beamforming is capable of providing significant performance gains in terms of a reduced bit error rate over MMSE beamforming. A block-data adaptive implementation of the MBER beamforming solution is developed based on the Parzen window estimate of probability density function. Furthermore, a sample-by-sample adaptive implementation is considered, and a stochastic gradient algorithm, referred to as the least bit error rate, is derived. The proposed adaptive MBER beamforming technique provides an extension to the existing work (Mulgrew and Chen 2001, Chen et al 2001} for adaptive MBER equalization and multiuser detection.
341-348
Chen, S.
9310a111-f79a-48b8-98c7-383ca93cbb80
Ahmad, N.N.
f6105bf9-7a9b-4e91-b1fa-4372662de087
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1
Chen, S.
9310a111-f79a-48b8-98c7-383ca93cbb80
Ahmad, N.N.
f6105bf9-7a9b-4e91-b1fa-4372662de087
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1

Chen, S., Ahmad, N.N. and Hanzo, L. (2005) Adaptive Minimum Bit Error Rate Beamforming. IEEE Transactions on Wireless Communications, 4 (2), 341-348.

Record type: Article

Abstract

An adaptive beamforming technique is proposed based on directly minimizing the bit error rate. It is demonstrated that this minimum bit error rate (MBER) approach utilizes the antenna array elements more intelligently, than the standard minimum mean square error (MMSE) approach. Consequently, MBER beamforming is capable of providing significant performance gains in terms of a reduced bit error rate over MMSE beamforming. A block-data adaptive implementation of the MBER beamforming solution is developed based on the Parzen window estimate of probability density function. Furthermore, a sample-by-sample adaptive implementation is considered, and a stochastic gradient algorithm, referred to as the least bit error rate, is derived. The proposed adaptive MBER beamforming technique provides an extension to the existing work (Mulgrew and Chen 2001, Chen et al 2001} for adaptive MBER equalization and multiuser detection.

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More information

Published date: March 2005
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 260714
URI: http://eprints.soton.ac.uk/id/eprint/260714
PURE UUID: 39c7a955-eae2-4be0-ad79-de04277726b0
ORCID for L. Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 04 Apr 2005
Last modified: 18 Mar 2024 02:33

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Contributors

Author: S. Chen
Author: N.N. Ahmad
Author: L. Hanzo ORCID iD

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