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计算机工程 ›› 2018, Vol. 44 ›› Issue (6): 50-56. doi: 10.19678/j.issn.1000-3428.0047190

• 移动互联与通信技术 • 上一篇    下一篇

一种基于特征值的3D MMSE角度域波束赋形算法

田明浩  a,刘仲康  a,冯永新  b,钱博  a   

  1. 沈阳理工大学a.信息科学与工程学院; b.研究生学院,沈阳 110159
  • 收稿日期:2017-05-12 出版日期:2018-06-15 发布日期:2018-06-15
  • 作者简介:田明浩(1977—),男,副教授、博士,主研方向为扩频通信技术及应用;刘仲康,硕士研究生;冯永新,教授、博士;钱博,副教授、博士。
  • 基金资助:

    辽宁省高等学校优秀人才支持计划项目(LJQ2014022);辽宁省教育厅科学研究项目(L2015462);新世纪优秀人才支持计划项目(NECT-11-1013);“辽宁省信息网络与信息对抗技术重点实验室”开放资金课题。

A 3D MMSE Angle Domain Beamforming Algorithm Based on Eigenvalue

TIAN Minghao  a,LIU Zhongkang  a,FENG Yongxin  b,QIAN Bo  a   

  1. a.School of Information Science and Engineering; b.Graduate School,Shenyang Ligong University,Shenyang 110159,China
  • Received:2017-05-12 Online:2018-06-15 Published:2018-06-15

摘要:

将传统二维角度域波束赋形算法应用于三维多输入多输出(3D MIMO)场景时,会导致波形畸变、不稳定甚至失效。为此,在传统二维最小均方误差算法的基础上,提出一种改进的3D MMSE角度域波束赋形算法。在面阵信号模型中利用特征分解法对信号相关矩阵进行分解,去除与噪声相关的小特征值扰动因子,以此解决波形畸变与算法失效问题。仿真结果表明,该算法可实现3D角度域波束赋形,相对3D MVDR算法和ZF算法,其阵列输出均方误差较小,信干噪比较高。

关键词: 散射信道, 角度域波束赋形, 波形畸变, 特征分解, 均方误差, 信干噪比

Abstract:

There are problems of waveform distortion,instability and even losing efficacy on condition that the beamforming algorithm of traditional two dimensional angular domain is applied to Three Dimensional Multiple Input Multiple Output(3D MIMO) scene.To solve the problem,on the basis of the traditional Two Dimensional Minimum Mean Square Error(2D MMSE) algorithm,an improved 3D MMSE angle domain beamforming algorithm is proposed,which applies the method of the eigen-decomposition to decompose the signal correlation matrix,removes the fluctuating factors in small eigenvalues associated with noise,and solves the issue of waveform distorting and losing efficacy.Simulation results show that the proposed algorithm can implement the beam forming in 3D angular domain,so that the MSE of array output is smaller and the Signal to Interference and Noise Ratio(SINR) of array output is higher than the 3D MVDR algorithm and the ZF algorithm.

Key words: scattering channels, angle domain beamforming, waveform distortion, eigen-decomposition, Mean Square Error(MSE), Signal to Interference and Noise Ratio(SINR)

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