Exploiting Reconfigurable Intelligent Surfaces for Performance Enhancement in 6G Wireless Networks

Abstract

Reconfigurable intelligent surfaces (RISs), with the potential to realize smart radio environments (SREs), have emerged as an energy-efficient and a cost-effective technology to support the services and demands foreseen for sixth generation (6G) wireless networks. By leveraging a large number of low-cost passives reflecting elements, RISs introduce a phase-shift in the impinging signal to create a favorable propagation channel between the transmitter and the receiver, thereby improving quality-of-service (QoS) and connectivity. The wireless environment that used to be a dynamic uncontrollable factor is now considered to be a part of the network design parameter. Inspired by the RIS potential to realize smart wireless environments and its compatibility with other technologies, in this thesis, we investigate the performance gains that can be achieved by integrating RIS with emerging communication technologies. Specifically, the research work, proposed systems models, and achieved contributions, based on the applications of RIS, are grouped into three research phases, as follows. In the first phase, we explore the application of RIS to cellular networks, which includes the secrecy performance analysis of the RIS-assisted aerial communication under practical constraints, i.e., imperfect channel state information (CSI) and discrete phase-shifts of the RIS, and the intelligent radio resource management in RIS-enabled multi-cluster non-orthogonal multiple access (NOMA) networks. In the second phase, the application of RIS to Internet-of-Things (IoT) networks is investigated. Specifically, we analyze the ergodic rate and bit error rate (BER) performance of the RIS-assisted NOMAenhanced backscatter communication (BAC-NOMA) system under Nakagami-m fading channels and element-splitting protocol of the RIS. Finally, taking into account the limitation of conventional reflecting-only RIS to provide half-space coverage, in the viii third phase, we explore the simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) for IoT networks. Specifically, we provide an effective capacity analysis for a STAR-RIS-assisted BAC-NOMA system under Nakagami-m fading and energy-splitting protocol of the STAR-RIS. Our research findings not only validate the efficacy of RIS technology but also offer practical insights for the design and optimization of RIS-assisted networks for 6G wireless communications, ensuring effective resource allocation and meeting the diverse system requirements.