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Genetic Algorithm Assisted Minimum Bit Error Rate Beamforming

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In this paper a novel Genetic Algorithm (GA) assisted Minimum Bit Error Rate Rate (MBER) beamforming technique is introduced. The performance of the proposed GAS is characterised by the Probability Density Function (PDF) and the mean value of the achievable Bit Error Rate @ER) at the beamformer's output. The results are also compared to the theoretical bounds. It is shown that GAS are suitable for MBER beamforming and that a trade-off between the complexity of the GA and its robustness against system parameter variations can be found.

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