Spatial diversity and channel statistics-based RF-baseband co-design for antenna selection

For MIMO systems, we introduce two novel architectures that significantly reduce the required number of expensive RF chains and still perform as well as a conventional full complexity solution for many cases of interest. We combine RF pre-processing - based solely on channel statistics and not instantaneous channel state - with selection and corresponding baseband signal processing. For a system with L RF chains, N_t transmit and N_r receive antennas, the first architecture uses an L×N_r RF pre-processing matrix that outputs only L streams followed by baseband signal processing. The second one uses an N_r×N_r RF pre-processing matrix followed by selection of L streams and baseband signal processing. We derive the optimal RF pre-processing matrices and the corresponding baseband combining vectors that maximize the average output SNR. A beamforming-based geometric intuition is also developed. With the constraints of today´s IC fabrication technology in mind, an approximation that requires only variable phase-shifters and adders, is also proposed and shown to incur a negligible loss in performance. In the process, a fair benchmark for comparing with the previously proposed FFT Butler pre-processing is provided.