TY - JOUR
T1 - Coverage Probability of Double-IRS Assisted Communication Systems
AU - Papazafeiropoulos, Anastasios
AU - Kourtessis, Pandelis
AU - Chatzinotas, Symeon
AU - Senior, John M.
N1 - Funding Information:
This work was supported in part by the University of Hertfordshire's 5-Year Vice Chancellor's Research Fellowship and in part by Luxembourg National Research Fund (FNR) under the CORE project RISOTTI under Grant C20/IS/14773976
Publisher Copyright:
© 2012 IEEE.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - In this letter, 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.
AB - In this letter, 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.
KW - beyond 5G networks
KW - cooperative passive beamforming
KW - coverage probability
KW - distributed IRSs
KW - Intelligent reflecting surface (IRS)
UR - http://www.scopus.com/inward/record.url?scp=85118249773&partnerID=8YFLogxK
U2 - 10.1109/LWC.2021.3121209
DO - 10.1109/LWC.2021.3121209
M3 - Article
AN - SCOPUS:85118249773
VL - 11
SP - 96
EP - 100
JO - IEEE Wireless Communications Letters
JF - IEEE Wireless Communications Letters
SN - 2162-2337
IS - 1
ER -