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