Ultra-dense network (UDN), as well as nonorthogonal multiple access (NOMA), has been emerging as promising techniques to meet the growing demand of data traffic in next-generation wireless networks. However, due to the spectrum sharing among SBSs and users, interference management (IM) is becoming a more important issue in NOMA-based UDN. Moreover, the massive small base stations (SBSs) with various types and overlapped coverage require more intelligent and efficient mechanisms for the IM problem. Thus, in this paper, to reduce interference and improve operation efficiency, we propose a self-optimizing resource allocation (SORA) scheme for IM with joint consideration of the dynamic interference conditions and fierce resource competition among SBSs. Concretely, each SBS constructs the interfering SBSs group adaptively to represent the potential interference from other SBSs. Then, to reduce interference and meet users' requirements, each SBS performs the resource allocation including sub-band and power allocation independently. Moreover, we formulate the problem as a non-cooperation satisfaction game, where a satisfaction function is established for evaluating each SBS's utility. When every SBS's utility is above a preset threshold, the game is considered to reach the satisfaction equilibrium. A distributed algorithm is designed to enable each SBS to learn the satisfaction equilibrium and allocate the resource autonomously. Simulation results show the effectiveness of the proposed scheme compared with the traditional schemes.

Additional Metadata
Keywords Interference management, Non-orthogonal multiple access (NOMA), Resource allocation, Self-optimizing, Ultra-dense network (UDN)
Persistent URL dx.doi.org/10.1109/WCNC.2018.8377038
Conference 2018 IEEE Wireless Communications and Networking Conference, WCNC 2018
Citation
Liu, Y. (Yiming), Yu, F.R, Li, X. (Xi), Ji, H. (Hong), Zhang, H. (Heli), & Leung, V.C.M. (Victor C.M.). (2018). Self-optimizing interference management for non-orthogonal multiple access in ultra-dense networks. In IEEE Wireless Communications and Networking Conference, WCNC (pp. 1–6). doi:10.1109/WCNC.2018.8377038