Coverage Probability of Double-IRS Assisted Communication Systems
Abstract
In this paper, we focus on the coverage probability of a double-intelligent reflecting surface (IRS) assisted wireless network and study the impact of multiplicative beamforming gain and correlated Rayleigh fading. In particular, we obtain a novel closed-form expression of the coverage probability of a single-input single-output (SISO) system assisted by two large IRSs while being dependent on the corresponding arbitrary reflecting beamforming matrices (RBMs) and large-scale statistics in terms of correlation matrices. Taking advantage of the large-scale statistics, i.e., statistical channel state information (CSI), we perform optimization of the RBMs of both IRSs once per several coherence intervals rather than at each interval. Hence, we achieve a reduction of the computational complexity, otherwise increased in multi-IRS-assisted networks during their RBM optimization. Numerical results validate the analytical expressions even for small IRSs, confirm enhanced performance over the conventional single-IRS counterpart, and reveal insightful properties.
Cite
@article{arxiv.2110.08317,
title = {Coverage Probability of Double-IRS Assisted Communication Systems},
author = {Anastasios Papazafeiropoulos and Pandelis Kourtessis and Symeon Chatzinotas and John M. Senior},
journal= {arXiv preprint arXiv:2110.08317},
year = {2021}
}
Comments
accepted in IEEE Wireless Communications Letters