Energy-Efficient and Distributed Resource Allocation for WPT Enabled Multicell Massive MIMO-NOMA Networks

Abstract

This paper investigates the energy-efficient resource allocation problem in multicell massive multiple input and multiple output (MIMO) non-orthogonal multiple access (NOMA) networks with wireless power transfer (WPT). In considered networks, Internet-of-Things (IoT) devices who have data packets to transmit in the uplink are charged by the wireless power harvested from the multi-antenna base stations (BSs) in the downlink. To adequately allocate the time of energy harvesting and data transmission, a time division protocol is proposed to divide downlink WPT and uplink wireless information transmission (WIT) time into two separate time slots. Aiming to obtain the optimal energy efficiency (EE) performance, we propose a joint power, time, subcarrier and antenna selection (AS) allocation scheme. An EE maximization problem is formulated to effectively determine the optimal resource allocation strategies. As the problem is nonconvex, we first invoke the nonlinear programming method to convert the problem into a convex optimization problem, and then solve it by taking an alternating direction method of multipliers (ADMM)-based distributed resource allocation algorithm. Simulation results demonstrate performance enhancement of the proposed algorithm over the benchmark schemes.