Developing NOMA to Next-Generation Multiple Access

Abstract

Due to the explosive growth in the number of wireless devices and diverse wireless services, such as virtual/augmented reality and Internet-of-Everything, next-generation wireless networks face unprecedented challenges caused by heterogeneous data traffic, massive connectivity, and ultra-high bandwidth efficiency plus ultra-low latency requirements. As a prominent member of the next-generation multiple access (NGMA) family, non-orthogonal multiple access (NOMA) has been recognized as a promising multiple access candidate for the sixth-generation (6G) networks. This chapter focuses on applying NOMA in 6G networks, with an emphasis on proposing the so-called One Basic Principle plus Four New concept. Starting with the basic NOMA principle, the importance of successive interference cancelation (SIC) becomes evident. In particular, the advantages and drawbacks of both the channel-state-information-based SIC and quality-of-service-based SIC are discussed. Then, the application of NOMA to meet the new 6G performance requirements, especially for massive connectivity, is explored. Furthermore, the integration of NOMA with new physical layer techniques is considered, followed by introducing new application scenarios for NOMA toward 6G. Finally, the application of machine learning in NOMA networks is investigated, ushering in the machine-learning-empowered NGMA era.