Journal
IEEE TRANSACTIONS ON NEURAL NETWORKS
Volume 19, Issue 9, Pages 1657-1663Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNN.2008.2000582
Keywords
beamforming; complex-valued radial basis function (RBF) network; multiple-antenna wireless system; symmetry; unsupervised clustering
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Funding
- Engineering and Physical Sciences Research Council [EP/D056691/1] Funding Source: researchfish
- EPSRC [EP/D056691/1] Funding Source: UKRI
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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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