Joint CSIT Acquisition Based on Low-Rank Matrix Completion for FDD Massive MIMO Systems

TL;DR

This paper introduces a joint CSIT acquisition method for FDD massive MIMO systems that leverages low-rank matrix completion to reduce overhead and improve accuracy in channel state information estimation.

Contribution

It proposes a novel joint CSIT recovery scheme using low-rank matrix completion, enabling direct feedback from users and reducing overhead compared to traditional methods.

Findings

Achieves accurate CSIT with lower overhead.

Utilizes low-rank property of MIMO channels.

Demonstrates improved performance through simulations.

Abstract

Channel state information at the transmitter (CSIT) is essential for frequency-division duplexing (FDD) massive MIMO systems, but conventional solutions involve overwhelming overhead both for downlink channel training and uplink channel feedback. In this letter, we propose a joint CSIT acquisition scheme to reduce the overhead. Particularly, unlike conventional schemes where each user individually estimates its own channel and then feed it back to the base station (BS), we propose that all scheduled users directly feed back the pilot observation to the BS, and then joint CSIT recovery can be realized at the BS. We further formulate the joint CSIT recovery problem as a low-rank matrix completion problem by utilizing the low-rank property of the massive MIMO channel matrix, which is caused by the correlation among users. Finally, we propose a hybrid low-rank matrix completion algorithm based on the singular value projection to solve this problem. Simulations demonstrate that the proposed scheme can provide accurate CSIT with lower overhead than conventional schemes.