Gridless Channel Estimation for MmWave Hybrid Massive MIMO Systems with Low-Resolution ADCs

TL;DR

This paper introduces a gridless compressed sensing channel estimator for mmWave hybrid massive MIMO systems with low-resolution ADCs, combining FCFGS and NOMP algorithms with cross validation for improved accuracy.

Contribution

It proposes a novel NFCFGS algorithm that performs gridless single path estimation and uses cross validation to determine the number of paths without prior knowledge.

Findings

Effective in estimating channels with low-resolution ADCs

Prevents overfitting through cross validation

Outperforms existing methods in accuracy and robustness

Abstract

This paper proposes the Newtonized fully corrective forward greedy selection-cross validation-based (NFCFGS-CV-based) channel estimator for millimeter (mmWave) hybrid massive multiple-input multiple-output (MIMO) systems with low-resolution analog-to-digital converters (ADCs). The proposed NFCFGS algorithm is a gridless compressed sensing (CS) technique that combines the FCFGS and Newtonized orthogonal matching pursuit (NOMP) algorithms. In particular, NFCFGS performs single path estimation over the continuum at each iteration based on the previously estimated paths. The CV technique is adopted as an indicator of termination in the absence of the prior knowledge on the number of paths, which is a model validation technique that prevents overfitting.