Simplified Robust Adaptive Detection and Beamforming for Wireless Communications

This book presents an alternative and simplified approaches for the robust adaptive detection and beamforming in wireless communications. It adopts several systems models including DS/CDMA, OFDM/MIMO with antenna array, and general antenna arrays beamforming model. It presents and analyzes recently developed detection and beamforming algorithms with an emphasis on robustness. In addition, simplified and efficient robust adaptive detection and beamforming techniques are presented and compared with exiting techniques. Practical examples based on the above systems models are provided to exemplify the developed detectors and beamforming algorithms. Moreover, the developed techniques are implemented using MATLAB—and the relevant MATLAB scripts are provided to help the readers to develop and analyze the presented algorithms.

Simplified Robust Adaptive Detection and Beamforming for Wireless Communications starts by introducing readers to adaptive signal processing and robust adaptive detection. It then goes on to cover Wireless Systems Models. The robust adaptive detectors and beamformers are implemented using the well-known algorithms including LMS, RLS, IQRD-RLS, RSD, BSCMA, CG, and SD. The robust detection and beamforming are derived based on the existing detectors/beamformers including MOE, PLIC, LCCMA, LCMV, MVDR, BSCMA, and MBER. The adopted cost functions include MSE, BER, CM, MV, and SINR/SNR.

Avainsanat:

adaptive signal processing; robust adaptive detection; radar signal processing; robust adaptive beamforming; wireless communications; sensor networks; array processing; digital signal processing; beamforming algorithms; DS/CDMA; OFDM/MIMO; antenna array; mobile communications; adaptive signal processing applications; robust adaptive detection/beamforming; robustness against uncertainty in DOA (direction-of-arrival); telecommunications; broadband networking; wireless systems models; adaptive detection algorithms; robust RLS adaptive algorithms; quadratically constrained robust detection; robust constant modulus algorithms; minimum BER adaptive detection