User Clustering Scheme for Downlink Hybrid NOMA Systems Based on Genetic Algorithm
Hanliang You, Zhiwen Pan, Nan Liu, Xiaohu You
Abstract
Non-orthogonal multiple access (NOMA) is considered to be a promising technology for improving bandwidth utilization efficiency and reducing power consumption. In this paper, we consider the optimization of user clustering in the NOMA scenario, where the goal is to maximize the system total throughput under minimum rate constraints. Different from most existing literatures, there is no limit on the number of users in each cluster. Simulation results show that the proposed scheme can significantly reduce computational complexity and have a better performance compared with schemes based on the other heuristic algorithms and random user clustering with greedy strategy.
Topics & Concepts
Computer scienceCluster analysisTelecommunications linkNomaGreedy algorithmComputational complexity theoryBandwidth (computing)HeuristicScheme (mathematics)ThroughputAlgorithmMathematical optimizationWirelessComputer networkMathematicsArtificial intelligenceMathematical analysisTelecommunicationsAdvanced Wireless Communication TechnologiesOptical Wireless Communication TechnologiesIoT Networks and Protocols