Machine Learning and Intelligent Communications. Third International Conference, MLICOM 2018, Hangzhou, China, July 6-8, 2018, Proceedings

Research Article

Optimal User Grouping and Resource Allocation for Downlink Non-Orthogonal Multiple Access Systems

  • @INPROCEEDINGS{10.1007/978-3-030-00557-3_53,
        author={Xiaoding Wang and Kejie Ni and Xiangxu Chen and Yuan Wu and Liping Qian and Liang Huang},
        title={Optimal User Grouping and Resource Allocation for Downlink Non-Orthogonal Multiple Access Systems},
        proceedings={Machine Learning and Intelligent Communications. Third International Conference, MLICOM 2018, Hangzhou, China, July 6-8, 2018, Proceedings},
        proceedings_a={MLICOM},
        year={2018},
        month={10},
        keywords={Bandwidth allocation Power allocation Non-orthogonal multiple access (NOMA) Successive interference cancellation (SIC)},
        doi={10.1007/978-3-030-00557-3_53}
    }
    
  • Xiaoding Wang
    Kejie Ni
    Xiangxu Chen
    Yuan Wu
    Liping Qian
    Liang Huang
    Year: 2018
    Optimal User Grouping and Resource Allocation for Downlink Non-Orthogonal Multiple Access Systems
    MLICOM
    Springer
    DOI: 10.1007/978-3-030-00557-3_53
Xiaoding Wang1,*, Kejie Ni1,*, Xiangxu Chen1,*, Yuan Wu1,*, Liping Qian1,*, Liang Huang1,*
  • 1: Zhejiang University of Technology
*Contact email: wxd_zjut@163.com, kjni_zjut@163.com, xxchen_zjut@163.com, iewuy@zjut.edu.cn, lpqian@zjut.edu.cn, lianghuang@zjut.edu.cn

Abstract

Non-orthogonal multiple access (NOMA) with successive interference cancellation (SIC) has recently been considered as a key enabling technique for 5G cellular networks to satisfy future users’ network needs, such as ultra-high transmission rate, ultra-high throughput, ultra-low latency and ultra-high density connections. A group of users is allowed to share the same spectrum and multiplex the power domain to transmit data. In this paper, we investigate the optimization of bandwidth allocation and user grouping under the conditions of transmission power limit, bandwidth allocation limit, and user traffic requirements, so that the total resource consumption is minimized. The key idea to solve the problem is to use the layer structure of the problem and divide the problem into the optimization grouping problem and the bandwidth allocation problem. We propose a simulated annealing algorithm to solve the optimization grouping problem.