Channel Estimation in Sub-6 GHz and Hybrid Millimeter Wave MIMO Systems With Low-Resolution ADCs

Abstract

This paper presents channel estimation strategies for the fifth generation (5G) new radio (NR) frequency bands i.e., sub-6 GHz for long range communications and millimeter wave (mmWave) frequency bands for medium to short range communications with low-resolution analog-to-digital converters (ADCs). For sub-6 GHz systems, we propose an energy-efficient iterative semi-blind channel estimation scheme for multi-user massive multiple-input multiple-output (MIMO) systems with low-resolution ADCs. The proposed semi-blind estimator improves the channel state information (CSI) accuracy with the addition of a few data symbols in the CSI acquisition process and concurrently enhances the spectral efficiency (SE) under the minimum pilot length constraint, unlike pilot training based schemes. We also derive an analytical expression for the lower bound on the uplink achievable rate of quantized massive MIMO sub-6 GHz systems. The energy efficiency (EE) and SE of the designed estimator for maximal ratio combining and zero-forcing receivers are also investigated. Furthermore, for the mmWave frequency band of 5G NR, we formulate a sparse Bayesian learning based frequency selective mmWave channel estimation scheme for MIMO systems equipped with hybrid architecture and low-resolution ADCs. The solidity of the proposed scheme is validated through extensive numerical results.