Intelligent Reflecting Surfaces-Assisted Cognitive NOMA in 5G/B5G Networks: Design, Architecture, Challenges, and Future Directions

The fifth-generation (5G) and beyond 5G (5G/B5G) wireless communication networks have prompted many challenges related to massive connectivity, high-speed transmission, spectrum efficiency, and energy efficiency. Utilizing cognitive radio (CR) technology and the non-orthogonal multiple access (NOMA) techniques can significantly improve system usage and performance as they support many users by allocating non-orthogonal resources and enable efficient spectrum utilization at the same time. Specifically, Cognitive NOMA networks offer a spectrum-efficient approach that exploits the licensed frequency bands opportunistically by altering the operating characteristics based on the surrounding radio frequency environment. However, such spectrum sharing and using non-orthogonal resources should be throttled to protect the quality of service (QoS) of the primary users (PUs) in such networks. Consequently, regulating the secondary users’ (SUs) transmit power is necessary, which might be detrimental to SU functionality. Intelligent reflecting surfaces (IRS), on the other hand, have emerged as a potentially game-changing technology for communication systems in recent years owing to their ability to boost both energy efficiency (EE) and spectral efficiency (SE) simultaneously. By strategically rearranging the signal’s path with inexpensive passive reflecting devices, IRS may significantly increase the range of wireless networks. This survey provides an overview of the IRS hardware design and analysis of the current state-of-the-art Cognitive NOMA and IRS-assisted Cognitive NOMA networks. It also presents the most important design challenges for deploying such networks. The survey concludes with a discussion of outstanding questions and suggestions for further investigation in this domain.