Artificial Intelligence (AI) Enabled NOMA
Recently, machine learning has been extensively applied in various areas including wireless communications. The more recent work has shown the power of deep learning in physical layer communications (Qin et al., IEEE Wireless Commun 26:93–99, 2019) and resource allocation (Ye et al., IEEE Veh Technol Mag 13:94–101, 2018). In this chapter, we will discuss the adaptive NOMA enabled by artificial intelligence AI and the new application of NOMA in the unmanned aerial vehicle (UAV) networks, with the goal to provide a potential solution to realize UAV networks with NOMA.
- Nikopour, H., & Baligh, H. (2013). Sparse code multiple access. In 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC) (pp. 332–336).Google Scholar
- Yuan, Z., Yu, G., Li, W., Yuan, Y., Wang, X., & Xu, J. (2016). Multi-user shared access for internet of things. In IEEE Proceedings of Vehicular Technology Conference (VTC).Google Scholar