Ergodic Capacity of Passive and Active IRS-Aided MIMO Systems

The intelligent reflecting surface (IRS) has emerged as a promising solution to address the ever-increasing demand for reliable and high-speed communication in next-generation wireless communication systems. In this article, the ergodic capacity (EC) of IRS-aided multiple-input-multiple-output (MIMO) wireless systems is investigated. Analytical approximations for the ECs of active and passive IRS-aided MIMO systems are derived. As an application of the established theoretical approximations, an optimization problem is formulated to maximize the system’s energy efficiency (EE) by determining the optimal number of IRS elements and the optimal transmission power. It is shown that this problem can be readily solved using an alternative optimization technique applicable to both active and passive IRS configurations. Numerical results demonstrate the accuracy of the EC approximations. The results also clarify the impact of operational and environmental parameters on the system’s EC.

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Publication Details

Journal
IEEE Sensors Journal
Published
2025-03-31
DOI
https://doi.org/10.1109/jsen.2025.3554445
Primary Topic
Advanced MIMO Systems Optimization
Type
article
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article

Ergodic Capacity of Passive and Active IRS-Aided MIMO Systems

Ali Olfat, Amir Masoud Rabiei, Hadi Gharibi
IEEE Sensors Journal
Advanced MIMO Systems Optimization
article

Ergodic Capacity of Passive and Active IRS-Aided MIMO Systems

Ali Olfat, Amir Masoud Rabiei, Hadi Gharibi
article en

Abstract

The intelligent reflecting surface (IRS) has emerged as a promising solution to address the ever-increasing demand for reliable and high-speed communication in next-generation wireless communication systems. In this article, the ergodic capacity (EC) of IRS-aided multiple-input-multiple-output (MIMO) wireless systems is investigated. Analytical approximations for the ECs of active and passive IRS-aided MIMO systems are derived. As an application of the established theoretical approximations, an optimization problem is formulated to maximize the system’s energy efficiency (EE) by determining the optimal number of IRS elements and the optimal transmission power. It is shown that this problem can be readily solved using an alternative optimization technique applicable to both active and passive IRS configurations. Numerical results demonstrate the accuracy of the EC approximations. The results also clarify the impact of operational and environmental parameters on the system’s EC.

IEEE Sensors JournalVol. 25(10)
University of Tehran (IR)
Affordable and clean energy
Openalex Percentile: Top 95%
Advanced MIMO Systems Optimization
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Ergodic Capacity of Passive and Active IRS-Aided MIMO Systems — Ali Olfat, Amir Masoud Rabiei, et al. · IEEE Sensors Journal (2025) | TGRS Research Map | TGRS