北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2020, Vol. 43 ›› Issue (3): 99-104.doi: 10.13190/j.jbupt.2019-195

• 研究报告 • 上一篇    下一篇

基于MBM的未编码空时标记分集技术

金宁1, 宋伟婧1, 金小萍1, 陈东晓1, 王嘉天2   

  1. 1. 中国计量大学 浙江省电磁波信息技术与计量检测重点实验室, 杭州 310018;
    2. 中国计量大学 信息工程学院, 杭州 310018
  • 收稿日期:2019-09-17 出版日期:2020-06-28 发布日期:2020-06-24
  • 通讯作者: 金小萍(1978-),女,副教授,E-mail:jxp1023@cjlu.edu.cn. E-mail:jxp1023@cjlu.edu.cn
  • 作者简介:金宁(1967-),女,教授.
  • 基金资助:
    浙江省自然科学基金项目(LY17F010012);浙江省教育厅科研资助项目(Y201840047);国家级大学生创新创业训练计划项目(201810356030)

Uncoded Space-Time Labeling Diversity Based on MBM

JIN Ning1, SONG Wei-jing1, JIN Xiao-ping1, CHEN Dong-xiao1, WANG Jia-tian2   

  1. 1. Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province, China Jiliang University, Hangzhou 310018, China;
    2. College of Information Engineering, China Jiliang University, Hangzhou 310018, China
  • Received:2019-09-17 Online:2020-06-28 Published:2020-06-24
  • Supported by:
     

摘要: 针对基于正交振幅调制(QAM)星座的未编码空时标记分集(USTLD)系统包络不恒定和频谱效率较低的问题,分别提出了相移键控星座的USTLD系统映射器设计方法和基于媒介调制(MBM)的USTLD系统,并对该系统的理论误码性能进行了分析.由于USTLD-MBM系统检测复杂度较高,故提出了该系统的低复杂度检测算法.仿真结果表明,在相同频谱效率的情况下,USTLD-MBM系统的误码性能优于USTLD系统.在USTLD-MBM系统中,球形译码算法的误码性能与最大似然算法几乎一致,复杂度降低了约50%.

关键词: 未编码空时标记分集, 媒介调制, 性能分析

Abstract: Aiming at the problem that the envelope of the uncoded space-time labeling diversity (USTLD) system based on quadrature amplitude modulation (QAM) constellation is not constant and the spectrum efficiency is low, the design method of mappers for phase shift keying (PSK) constellation and the USTLD system based on media based modulation (MBM) is proposed respectively. A bound of the average bit error probability of the proposed system is derived. Due to the high detection complexity of the USTLD-MBM system, a low complexity detection algorithm for the system is given. Simulations show that the error performance of the USTLD-MBM system is better than that of the USTLD system under the same spectral efficiency. In the USTLD-MBM system, the bit error performance (BER) of the sphere decoding algorithm is almost identical to the maximum likelihood (ML) algorithm, and the complexity is reduced by about 50%.

Key words: uncoded space-time labeling diversity, media based modulation, performance analysis

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