Downlink Channel Covariance Matrix Reconstruction for FDD Massive MIMO Systems with Limited Feedback

TL;DR

This paper introduces a novel algorithm for accurately reconstructing the downlink channel covariance matrix in FDD massive MIMO systems with limited feedback, improving performance in beamforming and user scheduling.

Contribution

It proposes a new formulation leveraging codebook structure and feedback, along with a cutting plane algorithm for CCM estimation, validated by theoretical and numerical results.

Findings

The algorithm accurately recovers the ground-truth CCM as communication rounds increase.

It outperforms existing benchmarks in CCM reconstruction.

Theoretical analysis confirms convergence with more communication rounds.

Abstract

The downlink channel covariance matrix (CCM) acquisition is the key step for the practical performance of massive multiple-input and multiple-output (MIMO) systems, including beamforming, channel tracking, and user scheduling. However, this task is challenging in the popular frequency division duplex massive MIMO systems with Type I codebook due to the limited channel information feedback. In this paper, we propose a novel formulation that leverages the structure of the codebook and feedback values for an accurate estimation of the downlink CCM. Then, we design a cutting plane algorithm to consecutively shrink the feasible set containing the downlink CCM, enabled by the careful design of pilot weighting matrices. Theoretical analysis shows that as the number of communication rounds increases, the proposed cutting plane algorithm can recover the ground-truth CCM. Numerical results are presented to demonstrate the superior performance of the proposed algorithm over the existing benchmark in CCM reconstruction.