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Clustering-Based Symmetric Radial Basis Function Beamforming

Clustering-Based Symmetric Radial Basis Function Beamforming
Clustering-Based Symmetric Radial Basis Function Beamforming
We propose a clustering-based symmetric radial basis function (SRBF) detector for multiple-antenna assisted beamforming systems. By exploiting the inherent symmetry of the underlying optimal Bayesian detection solution, this SRBF detector is capable of realizing the optimal Bayesian performance by clustering noisy observation data using an enhanced -means clustering algorithm. The proposed adaptive solution provides a signal-to-noise ratio gain in excess of 8 dB against the theoretical linear minimum bit error rate benchmark, when supporting five users with the aid of three receive antennas. Index Terms—Beamforming, clustering, multiple-antenna system, radial basis function network, symmetry.
589-592
Chen, S.
ac405529-3375-471a-8257-bda5c0d10e53
Labib, K.
38d604a0-10c0-4b45-9203-9b65b3927750
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1
Chen, S.
ac405529-3375-471a-8257-bda5c0d10e53
Labib, K.
38d604a0-10c0-4b45-9203-9b65b3927750
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1

Chen, S., Labib, K. and Hanzo, L. (2007) Clustering-Based Symmetric Radial Basis Function Beamforming. IEEE Signal Processing Letters, 14 (9), 589-592.

Record type: Article

Abstract

We propose a clustering-based symmetric radial basis function (SRBF) detector for multiple-antenna assisted beamforming systems. By exploiting the inherent symmetry of the underlying optimal Bayesian detection solution, this SRBF detector is capable of realizing the optimal Bayesian performance by clustering noisy observation data using an enhanced -means clustering algorithm. The proposed adaptive solution provides a signal-to-noise ratio gain in excess of 8 dB against the theoretical linear minimum bit error rate benchmark, when supporting five users with the aid of three receive antennas. Index Terms—Beamforming, clustering, multiple-antenna system, radial basis function network, symmetry.

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Published date: September 2007
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 264419
URI: http://eprints.soton.ac.uk/id/eprint/264419
PURE UUID: 3bb17855-0ee6-4360-8dbb-96a31704acfd
ORCID for L. Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

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

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