Intelligent Reflecting Surface-Enhanced OFDM: Channel Estimation and Reflection Optimization
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.
Cite
@article{arxiv.1909.03272,
title = {Intelligent Reflecting Surface-Enhanced OFDM: Channel Estimation and Reflection Optimization},
author = {Beixiong Zheng and Rui Zhang},
journal= {arXiv preprint arXiv:1909.03272},
year = {2020}
}
Comments
Early Access in IEEE Wireless Communications Letters. Please refer to "https://ieeexplore.ieee.org/document/8937491/". In this work, we propose practical a practical transmission protocol to execute optimal channel estimation and reflection optimization successively for an IRS-enhanced OFDM system, which is also applicable to the narrow-band IRS system