Massive MIMO With Downlink Energy Efficiency Operation in Industrial Internet of Things

Abstract

In this article, we present high energy-efficiency (EE) operation schemes for downlink orthogonal frequency division multiplexing (OFDM)-based massive multiple-input multiple-output (MIMO) systems in industrial Internet of Things (IIoT) networks. We derive the exact closed-form expressions for some important downlink operation parameters, and based on the parameters, we propose the methods of systematic operation to satisfy the required EE metric with low latency. The operation parameters include the number of service antennas, downlink transmission power, and related coverage. To increase the EE of downlink OFDM signal transmission, it is also well known that peak-to-average power ratio (PAPR) reduction is particularly important, and we apply the clipping PAPR reduction technique for the purpose to increase the power amplifier efficiency, and thus we also determine the level of clipping to satisfy the EE requirement. We use two representative linear precoding schemes for massive MIMO, such as maximum ratio (MR) precoding and zero-forcing (ZF) precoding, and show that the amount of clipping distortion of both MR precoding and ZF precoding is proportional to the distortion from the corresponding IIoT device's signal and distortions from other IIoT devices' signals. Simulation results are provided to validate the analysis and related schemes.