A comprehensive survey on spectrum sharing techniques for 5G/B5G intelligent wireless networks: Opportunities, challenges and future research directions

Abstract

Abstract

The increasing popularity of the Internet of Everything and small-cell devices has enormously accelerated traffic loads. Consequently, increased bandwidth and high data rate requirements stimulate the operation at the millimeter wave and the Tera-Hertz spectrum bands in the fifth generation (5G) and beyond 5G (B5G) wireless networks. Furthermore, efficient spectrum allocation, maximizing the spectrum utilization, achieving efficient spectrum sharing (SS), and managing the spectrum to enhance the system performance remain challenging. To this end, recent studies have implemented artificial intelligence and machine learning techniques, enabling intelligent and efficient spectrum leveraging. However, despite many recent research advances focused on maximizing utilization of the spectrum bands, achieving efficient sharing, allocation, and management of the enormous available spectrum remains challenging. Therefore, the current article acquaints a comprehensive survey on intelligent SS methodologies for 5G and B5G wireless networks, considering the applications of artificial intelligence for efficient SS. Specifically, a thorough overview of SS methodologies is conferred, following which the various spectrum utilization opportunities arising from the existing SS methodologies in intelligent wireless networks are discussed. Subsequently, to highlight critical limitations of the existing methodologies, recent literature on existing SS methodologies is reviewed in detail, classifying them based on the implemented technology, i.e., cognitive radio, machine learning, blockchain, and multiple other techniques. Moreover, the related SS techniques are reviewed to highlight significant challenges in the B5G intelligent wireless network. Finally, to provide an insight into the prospective research avenues, the article is concluded by presenting several potential research directions and proposed solutions.