Signal processing techniques for low-resolution ADC-based energy-efficient wireless communications

Abstract

We propose signal processing techniques for millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems with low-resolution analog-to-digital converters (ADCs). In particular, we shed light on how the channel model must be modified when low-resolution ADCs are used in the wideband setting - spatial wideband channel model - and propose a gridless channel estimator that estimates the angle parameters of the spatial wideband channel. In addition, we develop an optimal resource allocation scheme for cell-free mmWave massive MIMO systems with low-capacity fronthaul links and low-resolution ADC/DACs in the max-min fairness sense. Also, a Bayesian channel estimator is proposed for intelligent reflecting surface-aided (IRS-aided) mmWave massive MIMO systems with semi-passive elements.