IRS-Assisted Full Duplex Systems Over Rician and Nakagami Fading Channels

• Published in: IEEE open journal of vehicular technology Vol. 4; pp. 217 - 229
• Main Authors: Li, Suyue, Yan, Sen, Bariah, Lina, Muhaidat, Sami, Wang, Anhong
• Format: Journal Article
• Language: English
• Published: IEEE 2023
• Subjects: Full-duplex; Gamma distribution; intelligent reflecting surfaces; Nakagami distribution; non-reciprocal; Rayleigh channels; reciprocal; Relays; Rician and Nakagami fadings; Rician channels; Signal to noise ratio; Wireless communication
• ISSN: 2644-1330; 2644-1330
• DOI: 10.1109/OJVT.2022.3233857

Intelligent reflecting surface (IRS) has been deemed as an energy and spectral-efficient technology, that can potentially enhance network coverage and transmission reliability, with minimum impact on transceivers' complexity. Motivated by this, we develop a comprehensive analysis on the performance of integrating IRS into full-duplex (FD) cellular or Internet of Things (IoT) networks in both realistic Rician and Nakagami fadings. Firstly, in the context of reciprocal channels in Rician fadings, we derive the closed-form approximations of the users' outage probability (OP) and ergodic capacity (EC), under the non-central Chi-square distribution assumption on the signal-to-interference-plus-noise ratio (SINR). Further following by the Gamma distribution assumption on the SINR, we derive the cumulative distribution function (CDF) expression of the user's SINR, which is then leveraged to obtain simple yet effective closed-form expressions in terms of OP and EC. Subsequently, in Nakagami fading scenarios with the reciprocal and non-reciprocal channels, the closed forms of both users' OP and EC are obtained. Finally, the correctness of all the theoretical expressions is verified through substantial Monte Carlo simulations. The results indicate that the OP and EC deduced from Gamma distribution exhibit the fairly precise results for the arbitrary number of IRS elements, especially in Nakagami fadings.