Hybrid Transceiver Design and Optimal Power Allocation for the Cognitive mmWave Multiuser MIMO Downlink Relying on Limited Feedback

Abstract

A hybrid transceiver architecture is conceived for a cognitive radio (CR) aided millimeter wave (mmWave) multiuser (MU) multiple-input multiple-output (MIMO) downlink system relying on multiple radio frequency (RF) chains both at the CR base station (CBS) and the secondary users (SUs). To begin with, a hybrid transceiver design algorithm is proposed for the CBS and SUs, to maximize the sum spectral efficiency (SE) by decoupling the hybrid transceiver into a blind minimum mean squared error (MMSE) receiver combiner (RC) and optimal-capacity two-stage hybrid transmit precoder (TPC) components. These RC-weights and TPC-weights are subsequently found by using the popular simultaneous orthogonal matching pursuit (SOMP) technique. A closed-form solution is derived for the optimal power allocation that maximizes the sum SE under the associated interference and transmit power constraints. To achieve user fairness, we also propose an optimal power allocation scheme for maximizing the geometric mean (GM) of the SU rates. Finally, a low-complexity limited feedback aided hybrid transceiver is designed, which relies on the random vector quantization (RVQ) technique. Our simulation results demonstrate that an improved SE is achieved in comparison to the state-of-the-art techniques.

Keywords

• Millimeter wave
• cognitive radio
• multiple-input multiple-output (MIMO)
• hybrid beamforming
• sparse reconstruction