Coverage, Throughput, and Energy Efficiency Enhancement in Beamspace Massive MIMO System Using Rate-Splitting and Orthogonal Precoding

Millimeter-wave beamspace massive multiple-input multiple-output system with a lens antenna array can minimize transceiver hardware complexity without compromising performance. However, the number of supported portable user terminals cannot exceed the number of radio frequency blocks accessible at the same time, frequency, and coding resources. In this paper, we propose the integration of rate-splitting multiple access and orthogonal random precoding into the downlink of beamspace massive multiple-input multiple-output system to support a larger number of portable user terminals than the number of available radio frequency blocks while minimizing both inter- and intra-beam interferences and extending the cell coverage percentage. Then, we formulate an optimization problem to optimize the system’s overall throughput while keeping the minimum needed throughput and power budget in consideration. The nonconvex optimization issue is then approximated into a convex optimization problem using the successive convex approximation approach. Following that, we offer an alternating method to solve the approximate optimization issue and select an optimal solution. Furthermore, we deduce an analytic expression for the downlink cell coverage percentage and evaluate the effectiveness of the suggested method in terms of total throughput, energy efficiency, and cell coverage percentage. Finally, we compare the proposed method with benchmark techniques for perfect and imperfect channel state information, and numerical results confirm the superior performance of the proposed method over benchmark techniques in terms of sum throughput, energy efficiency, and cell coverage percentage.