Achievable Rate Optimization for Massive MIMO Enabled SWIPT Systems Over Downlink Rician Channels

This paper investigates the downlink transmission of massive multiple-input multiple-output-enabled simultaneous wireless information and power transfer systems in Rician fading channels. In the system, the base station is equipped with massive antennas to concurrently deliver information and energy to the users. While a portion of the harvested energy is utilized by the users to support the channel estimation, and the remaining is reserved as the supplement to the user battery for signal processing. The asymptotic expressions of the harvested energy and achievable rate are, respectively, derived, in the context of downlink scenario and line-of-sight propagation. With respect to the proposed system, two optimization problems are formulated, with the purposes of maximizing the system sum rate and the minimum rate among individual users, respectively. As both original problems are nonconvex and hard to solve, we propose a general iterative optimization framework to first decompose each of them into three subproblems, where the power allocation profiles, the channel estimation duration, and the power split ratios are optimized independently. The iteration is then carried out to update the solutions to each subproblem and finally approach the optimum of the original ones. The convergence and the effectiveness of the proposed algorithms are proved and evaluated through both theoretical analysis and simulations. Results demonstrate that the proposed algorithms can achieve the optimal transmission performance of the system with moderate complexity. Moreover, it can be further concluded that the maximum rate can be achieved if the harvested energy is fully devoted to pilot transmission.