User Clustering Scheme for Downlink Hybrid NOMA Systems Based on Genetic Algorithm

被引：23

作者：

You, Hanliang ^{[1
]}

Pan, Zhiwen ^{[1
,2
]}

Liu, Nan ^{[1
]}

You, Xiaohu ^{[1
,2
]}

机构：

[1] Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R China

[2] Purple Mt Labs, Nanjing 211100, Peoples R China

来源：

IEEE ACCESS | 2020年 / 8卷

关键词：

Non-orthogonal multiple access (NOMA); user clustering; genetic algorithm (GA); power allocation; NONORTHOGONAL MULTIPLE-ACCESS; MANAGEMENT; ALLOCATION;

D O I：

10.1109/ACCESS.2020.3009018

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：129461 / 129468

页数：8

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