电信科学 ›› 2016, Vol. 32 ›› Issue (8): 118-123.doi: 10.11959/j.issn.1000-0801.2016199

• 研究与开发 • 上一篇    下一篇

多小区大规模阵列天线系统盲解码算法

严斌彬1,沈雷1,2,姜显扬1,韩煜2   

  1. 1 杭州电子科技大学通信工程学院,浙江 杭州 310018
    2 中国电子科技集团公司第36研究所通信系统信息控制技术国家级重点实验室,浙江 嘉兴 314001
  • 出版日期:2016-08-20 发布日期:2017-04-26
  • 基金资助:
    国家自然科学基金资助项目;中国博士后科学基金资助项目;浙江省自然科学基金资助项目

Blind decoding method for a multi-cell massive antenna array system

Binbin YAN1,Lei SHEN1,2,Xianyang JIANG1,Yu HAN2   

  1. 1 School of Communications Engineering,Hangzhou Dianzi University,Hangzhou 310018,China
    2 State Key Lab of Information Control Technology in Communication System of No.36 Research Institute, China Electronic Technology Corporation,Jiaxing 314001,China
  • Online:2016-08-20 Published:2017-04-26
  • Supported by:
    The National Natural Science Foundation of China;China Postdoctoral Science Foundation;The Natural Science Foundation of Zhejiang Province of China

摘要:

针对多小区大规模阵列天线系统中干扰小区的导频复用造成的导频污染和解码性能下降问题,提出了基于ICA(独立分量分析)盲解码算法。所提盲解码算法,利用ICA法对接收多小区用户信号进行分离解码,不需要发射导频序列,避免了导频污染,提高了解码性能。所提盲解码算法在解码过程中同时估计各个用户波达方向,利用波达方向信息克服ICA方法分离顺序的不确定性,识别期望用户的信号。理论分析和仿真结果表明,所提盲解码方法比广泛应用的MMSE解码算法和最近提出的基于特征值的盲解码方法具有更好的性能。

关键词: 多小区, 大规模阵列天线, 盲解码, 独立分量分析

Abstract:

In order to overcome the pilot contamination and reduction of decoding performance resulted by neighbouring cell pilot sequences reuse in multi-cell massive array MIMO system,a blind decoding method based on ICA was proposed.The proposed blind decoding method used ICA to separate the received signals of multi-cell users without using pilot sequences.Thus,pilot contamination was avoided and decoding performance would be optimized.Every user’s angle-of-arrival(AOA)was estimated for recognizing the desired user signals and overcoming the uncertainty of signals separated by ICA.The analytical performance and numerical results show that the proposed method has a better performance compared to MMSE decoding and blind decoding method based on singular value decomposition(SVD).

Key words: multi-cell, massive antenna array, blind decoding, independent component analysis

No Suggested Reading articles found!