Intelligent Reflecting Surface-Enhanced OFDM: Channel Estimation and Reflection Optimization

TL;DR

This paper introduces a practical protocol for channel estimation and reflection optimization in IRS-enhanced OFDM systems, addressing the challenge of CSI acquisition with passive elements and demonstrating effective performance through simulations.

Contribution

It proposes a novel transmission protocol and reflection pattern design for IRS-OFDM systems, enabling efficient channel estimation and reflection optimization under practical constraints.

Findings

Closed-form channel estimation error derived

Low-complexity reflection coefficient optimization algorithm developed

Simulation results confirm effectiveness of the methods

Abstract

In the intelligent reflecting surface (IRS)-enhanced wireless communication system, channel state information (CSI) is of paramount importance for achieving the passive beamforming gain of IRS, which, however, is a practically challenging task due to its massive number of passive elements without transmitting/receiving capabilities. In this letter, we propose a practical transmission protocol to execute channel estimation and reflection optimization successively for an IRS-enhanced orthogonal frequency division multiplexing (OFDM) system. Under the unit-modulus constraint, a novel reflection pattern at the IRS is designed to aid the channel estimation at the access point (AP) based on the received pilot signals from the user, for which the channel estimation error is derived in closed-form. With the estimated CSI, the reflection coefficients are then optimized by a low-complexity algorithm based on the resolved strongest signal path in the time domain. Simulation results corroborate the effectiveness of the proposed channel estimation and reflection optimization methods.