Reducing Channel Estimation and Feedback Overhead in IRS-Aided Downlink System: A Quantize-then-Estimate Approach

TL;DR

This paper introduces a novel quantize-then-estimate protocol for IRS-aided downlink systems, significantly reducing pilot and feedback overhead by exploiting channel correlations, with analytical proof of performance improvements.

Contribution

It proposes a new quantize-then-estimate approach for downlink IRS systems, leveraging channel correlation to reduce overhead, unlike traditional methods.

Findings

Reduces pilot and feedback overhead compared to conventional schemes.

Achieves efficient channel estimation by exploiting channel correlation.

Provides analytical quantification of performance gains.

Abstract

Channel state information (CSI) acquisition is essential for the base station (BS) to fully reap the beamforming gain in intelligent reflecting surface (IRS)-aided downlink communication systems. Recently, [1] revealed a strong correlation in different users' cascaded channels stemming from their common BS-IRS channel component, and leveraged such a correlation to significantly reduce the pilot transmission overhead in IRS-aided uplink communication. In this paper, we aim to exploit the above channel property to reduce the overhead for both pilot and feedback transmission in IRS-aided downlink communication. Note that in the downlink, the distributed users merely receive the pilot signals containing their own CSI and cannot leverage the correlation in different users' channels, which is in sharp contrast to the uplink counterpart considered in [1]. To tackle this challenge, this paper proposes a novel ``quantize-then-estimate'' protocol in frequency division duplex (FDD) IRS-aided downlink communication. Specifically, the users quantize and feed back their received pilot signals, instead of the estimated channels, to the BS. After de-quantizing the pilot signals received by all the users, the BS estimates all the cascaded channels by leveraging their correlation, similar to the uplink scenario. Under this protocol, we manage to propose efficient user-side quantization and BS-side channel estimation methods. Moreover, we analytically quantify the pilot and feedback transmission overhead to reveal the significant performance gain of our proposed scheme over the conventional ``estimate-then-quantize'' scheme.