Energy-Efficient Resource Allocation in Massive MIMO-NOMA Networks With Wireless Power Transfer: A Distributed ADMM Approach

In multicell massive multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) networks, base stations (BSs) with antennas deliver their radio frequency energy in the downlink, and Internet-of-Things (IoT) devices use harvested to support uplink data transmission. This paper investigates efficiency (EE) problem for MIMO NOMA networks wireless power transfer (WPT). To maximize EE of network, we propose a novel joint power, time, antenna selection, subcarrier resource allocation scheme, which can properly allocate time harvesting Both perfect imperfect channel state information (CSI) are considered, corresponding performance is analyzed. Under quality-of-service (QoS) requirements, an maximization formulated, non-trivial due non-convexity. We first adopt nonlinear fraction programming methods convert be convex, then, develop distributed alternating direction method multipliers (ADMM)- based approach solve problem. Simulation results demonstrate that compared alternative methods, proposed algorithm converge quickly within fewer iterations, achieve better performance.