Low complexity detection based on selective message passing for SCMA systems

被引:3
|
作者
Wu, Hanguang [1 ]
Xiong, Xiaoming [1 ]
Gao, Huaien [1 ]
机构
[1] Guangdong Univ Technol, Guangzhou, Guangdong, Peoples R China
关键词
error statistics; 5G mobile communication; low complexity detection; selective message passing; SCMA systems; sparse code multiple access systems; multiuser detection schemes; BER; computational complexity;
D O I
10.1049/el.2018.0125
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The sparse code multiple access (SCMA) systems rely on multiuser detection schemes to achieve high spectral efficiency and massive connectivity. The existing multiuser detection schemes employ a message passing algorithm (MPA) to achieve the goal by utilising the sparse structure of the SCMA codebook. However, it remains a challenging task to obtain a good trade-off between the BER performance and computational complexity due to the iterative nature and the associated search space in the MPA detection. In this Letter, a novel MPA detection scheme based on selective message passing is proposed. By dynamically eliminating the branches with high reliability from the message passing process, the proposed scheme significantly reduces the computational complexity with negligible BER performance compared with the conventional MPA detection. Simulation results show that the proposed scheme is able to achieve a good trade-off between the BER performance and computational complexity, especially at moderate and high signal-to-noise ratio conditions.
引用
收藏
页码:533 / 534
页数:2
相关论文
共 50 条
  • [41] A Low Complexity SCMA Detector Based on Avoiding Redundant Iterations
    Hao, Shuliang
    Su, Xin
    Zeng, Jie
    Ma, Xin
    Lv, Tiejun
    2018 12TH INTERNATIONAL SYMPOSIUM ON MEDICAL INFORMATION AND COMMUNICATION TECHNOLOGY (ISMICT), 2018, : 217 - 221
  • [42] A Low-Complexity Cooperative Localization Algorithm based on Variational Message Passing in Wireless Networks
    Yuan, Weijie
    Wu, Nan
    Li, Bin
    Wang, Hua
    Kuang, Jingming
    2014 SIXTH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS AND SIGNAL PROCESSING (WCSP), 2014,
  • [43] Low Complexity Uplink Grant-Free NOMA Based on Boosted Approximate Message Passing
    Hara, Takanori
    Ishibashi, Koji
    CONFERENCE RECORD OF THE 2019 FIFTY-THIRD ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, 2019, : 1877 - 1880
  • [44] Low Complexity Expectation Propagation Detection for SCMA Using Approximate Computing
    Xiao, Jie
    Hu, Jianhao
    Han, Kaining
    2019 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2019,
  • [45] A Low Complexity Reliability-Aware Based Expectation Propagation Algorithm for Uplink SCMA Systems
    Dong, Yuanyuan
    Li, Hua
    Zhang, Zhenyu
    Zhao, Shuang
    Wang, Xiyuan
    Zou, Runmin
    Dai, Xiaoming
    PROCEEDINGS OF 2018 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS (ICCS 2018), 2018, : 35 - 39
  • [46] Low-Complexity Precoding Design for Massive Multiuser MIMO Systems Using Approximate Message Passing
    Chen, Jung-Chieh
    Wang, Chang-Jen
    Wong, Kai-Kit
    Wen, Chao-Kai
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2016, 65 (07) : 5707 - 5714
  • [47] A Low-Complexity Gaussian Message Passing Iterative Detector for Massive MU-MIMO Systems
    Liu, Lei
    Yuen, Chau
    Guan, Yong Liang
    Li, Ying
    Su, Yuping
    2015 10TH INTERNATIONAL CONFERENCE ON INFORMATION, COMMUNICATIONS AND SIGNAL PROCESSING (ICICS), 2015,
  • [48] A low complexity OFDM receiver with combined GAMP and MF message passing
    Zhengdao Yuan
    Chuanzong Zhang
    Zhongyong Wang
    Qinghua Guo
    Sheng Wu
    Telecommunication Systems, 2019, 71 : 425 - 432
  • [49] A low complexity OFDM receiver with combined GAMP and MF message passing
    Yuan, Zhengdao
    Zhang, Chuanzong
    Wang, Zhongyong
    Guo, Qinghua
    Wu, Sheng
    TELECOMMUNICATION SYSTEMS, 2019, 71 (03) : 425 - 432
  • [50] Multi-stage Message Passing Algorithm for SCMA downlink Receiver
    Zhang, Han
    Han, Shuai
    Meng, Wei-Xiao
    2016 IEEE 84TH VEHICULAR TECHNOLOGY CONFERENCE (VTC FALL), 2016,