Evolutionary computational intelligence methods have found wide-ranging application in communication and other walks of engineering. The main attraction of adopting evolutionary computational intelligence algorithms is that they may facilitate global or near global optimal designs with affordable computational costs. This contribution considers the beamforming assisted multiple-antenna receiver for multi-user quadrature amplitude modulation systems. The bit error rate (BER) expression as the function of the beamformer's weight vector is derived explicitly. The minimum BER (MBER) beamforming receiver can then be obtained as the solution of the resulting optimisation problem that minimises the MBER criterion. We propose to employ a differential evolution algorithm to solve the MBER optimisation by its virtue of computational efficiency and ability to locate a global minimum quickly.
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