State of the Art, Taxonomy, and Open Issues on Cognitive Radio Networks with NOMA

The explosive growth of mobile devices and the rapid increase of wideband wireless services call for advanced communication techniques that can achieve high spectral efficiency and meet the massive connectivity requirement. Cognitive radio (CR) and non-orthogonal multiple access (NOMA) are envisioned to be important solutions for the fifth generation wireless networks. Integrating NOMA techniques into CR networks (CRNs) has the tremendous potential to improve spectral efficiency and increase the system capacity. However, there are many technical challenges due to the severe interference caused by using NOMA. Many efforts have been made to facilitate the application of NOMA into CRNs and to investigate the performance of CRNs with NOMA. This article aims to survey the latest research results along this direction. A taxonomy is devised to categorize the literature based on operation paradigms, enabling techniques, design objectives and optimization characteristics. Moreover, the key challenges are outlined to provide guidelines for the domain researchers and designers to realize CRNs with NOMA. Finally, the open issues are discussed. Fuhui Zhou and Yuhao Wang are with the School of Information Engineering, Nanchang University, Nanchang, 330031, China, (e-mail: [email protected], [email protected]). Yongpeng Wu is with Shanghai Key Laboratory of Navigation and Location Based Services, Shanghai Jiao Tong University, Minhang, 200240, China (Email:[email protected]). Ying-Chang Liang is with University of Sydney, Sydney, NSW 2006, Australia, and University of Electronic Science and Technology of China, Chengdu, China ([email protected]). Zan Li is with the Integrated Service Networks Lab of Xidian University, Xian, 710071, China (e-mail: [email protected]). Kai-Kit Wong is with the Department of Electronic and Electrical Engineering, University College London, WC1E 7JE, United Kingdom (e-mail: [email protected]). TThe research was supported by the National Natural Science Foundation of China (61701214, 61701301, 61661028, 61631015, 61561034, 61761030 and 61501356) The Young Natural Science Foundation of Jiangxi Province (20171BAB212002), the China Postdoctoral Science Foundation (2017M610400), and The Postdoctoral Science Foundation of Jiangxi Province (2017KY04). ar X iv :1 80 1. 01 99 7v 1 [ cs .N I] 6 J an 2 01 8