An Efficient CSI Acquisition Method for Intelligent Reflecting Surface-assisted mmWave Networks

TL;DR

This paper introduces a low-complexity, resource-efficient channel acquisition method for IRS-assisted mmWave networks, leveraging channel sparsity and IRS topology to improve estimation accuracy and reduce resource consumption.

Contribution

It presents a novel channel estimation technique that significantly reduces resource usage by exploiting mmWave channel sparsity and IRS structure, outperforming existing methods.

Findings

Requires less time-frequency resource for channel estimation

Achieves large performance gains in simulations

Proves effectiveness of the proposed method

Abstract

Millimeter-wave (mmWave) communication is one of the key enablers of the fifth-generation cellular networks (5G). However, one of the fundamental challenges of mmWave communication is the susceptibility to blockage effects. One way to alleviate this effect is the use of Intelligent Reflecting Surface (IRS). Nevertheless, due to the large number of the reflecting elements on IRS, the channel estimation turns out to be a challenging problem. This paper proposes a low-complexity channel information acquisition method for IRS-assisted mmWave communication system. Our idea consists in exploiting the sparsity of the mmWave channel and the topology of IRS itself. Compared to the state-of-the-art methods, our proposed method requires much less time-frequency resource in the acquisition of channel information. Large performance gains are confirmed in simulation, which prove the effectiveness of our proposed method.