Adaptive minimum entropy beamformer for wireless communication

A novel adaptive beamformer is proposed for wireless communication application based on error-entropy minimization algorithm. The beamforming processing is done classically by minimizing the mean square error (MSE) between the desired signals and actual array outputs. The MSE beamformer, which uses only second-order statistics, can provide good performance and can readily be implemented usually. However, the transmission performance of the MSE beamformer degrades under severe channel, such as strong interference condition or severe noise. In this paper, the minimum entropy beamformer that considers all the higher order statistics of the error is proposed. Simulation results show that proposed beamforming technique can reach lower BER compared to the minimum MSE beamforming technique under severe channel. Furthermore, the minimum entropy beamformer can provide fast convergence and is adequate for next generation of wireless communication.