TY - JOUR
T1 - Ergodic Capacity of IRS-Assisted MIMO Systems with Correlation and Practical Phase-Shift Modeling
AU - Papazafeiropoulos, Anastasios
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 the National Research Fund, Luxembourg, through the Project RISOTTI.
Publisher Copyright:
© 2012 IEEE.
PY - 2022/2/1
Y1 - 2022/2/1
N2 - We focus on the maximization of the exact ergodic capacity (EC) of a point-to-point multiple-input multiple-output (MIMO) system assisted by an intelligent reflecting surface (IRS). In addition, we account for the effects of correlated Rayleigh fading and the intertwinement between the amplitude and the phase shift of the reflecting coefficient of each IRS element, which are usually both neglected despite their presence in practice. Random matrix theory tools allow to derive the probability density function (PDF) of the cascaded channel in closed form, and subsequently, the EC, which depend only on the large-scale statistics and the phase shifts. Notably, we optimize the EC with respect to the phase shifts with low overhead, i.e., once per several coherence intervals instead of the burden of frequent necessary optimization required by expressions being dependent on instantaneous channel information. Monte-Carlo (MC) simulations verify the analytical results and demonstrate the insightful interplay among the key parameters and their impact on the EC.
AB - We focus on the maximization of the exact ergodic capacity (EC) of a point-to-point multiple-input multiple-output (MIMO) system assisted by an intelligent reflecting surface (IRS). In addition, we account for the effects of correlated Rayleigh fading and the intertwinement between the amplitude and the phase shift of the reflecting coefficient of each IRS element, which are usually both neglected despite their presence in practice. Random matrix theory tools allow to derive the probability density function (PDF) of the cascaded channel in closed form, and subsequently, the EC, which depend only on the large-scale statistics and the phase shifts. Notably, we optimize the EC with respect to the phase shifts with low overhead, i.e., once per several coherence intervals instead of the burden of frequent necessary optimization required by expressions being dependent on instantaneous channel information. Monte-Carlo (MC) simulations verify the analytical results and demonstrate the insightful interplay among the key parameters and their impact on the EC.
KW - beyond 5G networks
KW - correlated Rayleigh fading
KW - ergodic capacity
KW - Intelligent reflecting surface (IRS)
KW - MIMO communication
UR - http://www.scopus.com/inward/record.url?scp=85120569428&partnerID=8YFLogxK
U2 - 10.1109/LWC.2021.3131401
DO - 10.1109/LWC.2021.3131401
M3 - Article
AN - SCOPUS:85120569428
SN - 2162-2337
VL - 11
SP - 421
EP - 425
JO - IEEE Wireless Communications Letters
JF - IEEE Wireless Communications Letters
IS - 2
ER -