Low-complexity optimization based algorithm for maximum likelihood multi-user detection

被引：0
作者：
Tuan, HD [1 ]
Son, TT [1 ]
Tuy, H [1 ]
Ngoc, TL [1 ]
机构：
[1] Toyota Technol Inst, Dept Elect & Comp Engn, Nagoya, Aichi 468, Japan
来源：
5TH INTERNATIONAL SYMPOSIUM ON WIRELESS PERSONAL MULTIMEDIA COMMUNICATIONS, VOLS 1-3, PROCEEDINGS | 2002年
关键词：
multi-user detection; concave programming;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The multiuser detection (MUD) problem is revealed concave in nature. Then, a new concave programming-based algorithm for MUD is proposed. Our intensive simulation clearly shows that it outperforms all previously developed algorithms while the computational burden is essentially reduced.
引用
收藏
页码：1222 / 1226
页数：5
相关论文
共 50 条
  • [21] Bayesian Blind Detection Algorithm Based on Multi-User Serial Interference Cancellation
    Wu Q.
    Si Z.
    Dai J.
    Wang S.
    Yuan Y.
    Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications, 2024, 47 (01): : 1 - 6and37
  • [22] Sparse Bayesian learning-based massive multi-user detection algorithm
    Chen P.
    Wang X.
    Xie Z.
    Fang Y.
    Chen J.
    Tongxin Xuebao/Journal on Communications, 2023, 44 (10): : 186 - 197
  • [23] Multi-User Joint Maximum-Likelihood Detection in Uplink NOMA-IoT Networks: Removing the Error Floor
    Semira, Hichem
    Kara, Ferdi
    Kaya, Hakan
    Yanikomeroglu, Halim
    IEEE WIRELESS COMMUNICATIONS LETTERS, 2021, 10 (11) : 2459 - 2463
  • [24] Low Complexity Suboptimal Constellation Design for Multi-User Multiple Access
    Hao, Xing
    Xiao, Yu
    Wu, Yuteng
    Zhang, Qinbo
    Atkin, G. E.
    2020 IEEE INTERNATIONAL CONFERENCE ON ELECTRO INFORMATION TECHNOLOGY (EIT), 2020, : 259 - 263
  • [25] Application of a genetic algorithm to Hopfield network multi-user detection
    Zhang, Y
    Liu, HL
    Kuang, F
    Chen, J
    2005 INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING PROCEEDINGS, VOLS 1 AND 2, 2005, : 644 - 647
  • [26] A Method for Analysing and Improving the Multi-user Detection Algorithm of SCMA
    Han, Shuai
    Huang, Yiteng
    Wang, Bin
    WIRELESS INTERNET (WICON 2017), 2018, 230 : 103 - 115
  • [27] Convex optimization-based multi-user detection in underwater acoustic sensor networks
    Wang, Jianping
    Zhang, Shujing
    Chen, Wei
    Kong, Dechuan
    Yu, Zhou
    INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2018, 14 (02):
  • [28] An Improved Subspace-based Group-Blind Multi-user Detection Algorithm
    Jia Li-qin
    Xu Yan-ping
    THIRD INTERNATIONAL SYMPOSIUM ON ELECTRONIC COMMERCE AND SECURITY WORKSHOPS (ISECS 2010), 2010, : 300 - 302
  • [29] Multi-User Detection In DS-CDMA System Using Biogeography Based Optimization
    Nemade, Santosh N.
    Kolte, Mahesh T.
    Nemade, Santosh
    PROCEEDINGS OF 4TH INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATION AND CONTROL(ICAC3'15), 2015, 49 : 289 - 297
  • [30] The neural network multi-user detection based on MMSE
    Li, Yanpin
    Peng, Jisheng
    Wang, Huakui
    2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23, 2008, : 5896 - 5900
12345