Robust Wideband Channel Estimation for mmWave Massive MIMO Systems With Beam Squint

TL;DR

This paper presents a robust wideband channel estimation method for mmWave massive MIMO systems that effectively addresses beam squint and impulsive noise, outperforming existing techniques.

Contribution

It introduces a novel estimation approach using cyclic refinement and generalized _p-norm minimization to enhance robustness against non-Gaussian noise and beam squint effects.

Findings

Proposed method outperforms benchmarks in numerical tests.

Enhanced robustness to impulsive noise demonstrated.

Effective mitigation of beam squint effects.

Abstract

This paper investigates the robust wideband channel estimation problem in the millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems. In such a scenario, the beam squint effect that the array response vectors vary with different frequencies and the impulsive noise are in existence, which pose great challenges for accurate channel estimation. Directly applying the existing channel estimation methods usually suffers significant performance degradation, since they are proposed based on the assumptions of frequency-invariant array response vectors and Gaussian distributed noise. To address these issues, this paper proposes a novel wideband channel estimation method with robustness to impulsive noise. Specifically, the proposed method incorporates a cyclic refinement step to overcome the estimation inaccuracy caused by the greedy nature of matching-pursuit-esque algorithms. In particular, the generalized $\ell_p$-norm minimization criterion is adopted in Newton's method to improve the performance robustness against the non-Gaussian impulsive noise. Numerical results are provided to verify the superior performance of the proposed method over the existing representative benchmarks.