Channel Estimation for TDD/FDD Massive MIMO Systems with Channel Covariance Computing

TL;DR

This paper introduces a novel channel estimation method for massive MIMO systems that reconstructs channel covariance matrices using array signal processing, improving estimation accuracy without extra training.

Contribution

It presents a new covariance reconstruction approach leveraging angle and PAS reciprocity, applicable to TDD and FDD systems with various array geometries.

Findings

Improved uplink channel estimation accuracy.

Effective downlink CSI inference for FDD systems.

Superiority over existing methods demonstrated through simulations.

Abstract

In this paper, we propose a new channel estimation scheme for TDD/FDD massive MIMO systems by reconstructing uplink/downlink channel covariance matrices (CCMs) with the aid of array signal processing techniques. Specifically, the angle information and power angular spectrum (PAS) of each multi-path channel is extracted from the instantaneous uplink channel state information (CSI). Then, the uplink CCM is reconstructed and can be used to improve the uplink channel estimation without any additional training cost. In virtue of angle reciprocity as well as PAS reciprocity between uplink and downlink channels, the downlink CCM could also be inferred with a similar approach even for FDD massive MIMO systems. Then, the downlink instantaneous CSI can be obtained by training towards the dominant eigen-directions of each user. The proposed strategy is applicable for any kind of PAS distributions and array geometries. Numerical results are provided to demonstrate the superiority of the proposed methods over the existing ones.