Performance Analysis of CF-mMIMO-Aided SWIPT IoT Networks With Nonideal RF Response and Low-Resolution ADCs/DACs
Yao Zhang, Kaixi Yang, Wenchao Xia, Haitao Zhao, Xiuling Xu, Lina Chen, Hong Gao
Abstract
This article investigates the downlink performance of a cell-free massive multiple-input multiple-output (CF-mMIMO)-aided simultaneous wireless information and power transfer Internet-of-Things (SWIPT-IoT) network. Considering a more practical scenario with non-ideal radio frequency responses and low-resolution analog-to-digital converters (ADCs) and digital-to-analog converters (DACs), closed-form expressions for the lower-bound achievable rate and harvested energy (HE) under conjugate beamforming (CB) and enhanced normalized CB (ECB) schemes are derived. By virtue of these closed-form results, we conduct comprehensive HE and rate performance analyses with respect to various system parameters. To further enhance the downlink rate performance, a novel hybrid precoding scheme that combines the benefits of both CB and ECB is proposed. Aside from the above, we also develop a particle swarm optimization (PSO) framework in terms of ADC/DAC resolution to maximize the sum-HE and sum-rate. All theoretical analyses and the performance of the proposed optimization algorithm are validated via extensive simulations.