Variable Step-size Zero Attractor LMS based Channel Estimator for Millimeter Wave Hybrid MIMO System with Hardware Impairments

Abstract

Millimeter wave (mmWave) multiple-input multiple-output (MIMO) is a potential physical layer technology for the fifth and the sixth-generation (5G/6G) wireless communication systems. However, existing works in mmWave hybrid processing do not adequately address the impact of unavoidable residual transceiver hardware impairments (RTHI). In this paper, channel estimation in an RTHI-affected channel in the mmWave hybrid MIMO system is investigated. Due to the RTHI, pilot and received information signals gets deteriorated, which makes channel estimation extremely challenging. Greedy-based iterative methods like orthogonal matching pursuit (OMP) and classical channel estimation techniques such as least squares (LS) provide very high computational complexity due to inversions of large matrices. We, therefore, provide a variable step-size zero-attracting least mean square (VSS-ZALMS) based channel estimator for the system under consideration to overcome these difficulties. Simulation results show that the proposed estimation algorithm significantly outperforms in terms of computational complexity and error performance compared to OMP, Bayesian compressive sensing (BCS), and sparse Bayesian learning (SBL). © 2023 IEEE.