计算机应用 ›› 2018, Vol. 38 ›› Issue (8): 2370-2374.DOI: 10.11772/j.issn.1001-9081.2018010138

• 网络与通信 • 上一篇    下一篇

非理想信道状态信息下权值可调干扰对齐算法

徐栋, 李勇, 刘东东, 鲁亚凯   

  1. 移动通信技术重点实验室(重庆邮电大学), 重庆 400065)
  • 收稿日期:2018-01-17 修回日期:2018-03-15 出版日期:2018-08-10 发布日期:2018-08-11
  • 通讯作者: 徐栋
  • 作者简介:徐栋(1991-),男,湖北黄冈人,硕士研究生,主要研究方向:干扰对齐、天线选择;李勇(1970-),男,重庆人,高级工程师,硕士,主要研究方向:干扰对齐;刘东东(1990-),男,安徽淮北人,硕士研究生,主要研究方向:低功耗有损网络路由协议;鲁亚凯(1990-),男,河南商丘人,硕士研究生,主要研究方向:空中下载、双通道升级。
  • 基金资助:
    长江学者和创新团队发展计划项目(IRT1299);重庆市科委项目(cstc2013yykfA40010)。

Weight adjustable interference alignment algorithm with imperfect channel state information

XU Dong, LI Yong, LIU Dongdong, LU Yakai   

  1. Chongqing Key Laboratory of Mobile Communications Technology(Chongqing University of Posts and Communications), Chongqing 400065, China
  • Received:2018-01-17 Revised:2018-03-15 Online:2018-08-10 Published:2018-08-11
  • Supported by:
    This work is partially supported by the Program for Changjiang Scholars and Innovative Research Team in University (IRT1299), the Chongqing Municipal Science and Technology Commission Key Laboratory of Special Funded Projects (cstc2013yykfA4001).

摘要: 针对多输入多输出(MIMO)系统获取信道信息过程中存在估计误差、反馈延迟等问题,为了提高低信噪比(SNR)时的系统性能,提出了一种基于权值可调的稳健干扰对齐算法。首先,在理想信道的基础上考虑信道误差的影响重新构建系统模型;然后,采用矩阵投影技术对接收端的信号空间进行分解,分成期望信号子空间与干扰信号子空间两部分;其次,考虑期望信号和干扰信号之间的相互影响,把两者泄漏到相应的子空间的功率加权和作为目标函数运用迭代思想计算出预编码和干扰抑制矩阵;最后,利用计算出的预编码和干扰抑制矩阵推导出存在信道误差的和速率表达式。仿真结果表明与稳健最小干扰泄漏算法相比,在信噪比为10 dB、信道误差方差取值0.05时,系统的频谱效率提升了25%,能量效率提升了38%,因此所提算法在低信噪比时可以有效地提升系统性能。

关键词: 无线通信, 信道误差, 稳健干扰对齐, 低信噪比, 系统和速率

Abstract: For the problem of estimation error and feedback delay in the process of acquiring channel information in Multiple-Input Multiple-Output (MIMO) systems, a robust interference alignment algorithm based on weight adjustment was proposed to improve the system performance at low Signal-to-Noise Ratio (SNR). Firstly, the system model was reconstructed by considering the influence of channel error on the basis of the ideal channel; secondly, the signal space at the receiving terminal was decomposed by matrix projection and divided into two parts, including desired signal subspace and interference signal subspace; thirdly, considering the interaction between the desired signal and the interference signal, the weighted sum of the power leaked into the corresponding subspaces was used as the objective function, and the iterative idea was used to calculate the precoding and interference suppression matrix. Finally, the calculated pre-coding and interference suppression matrix was used to derive the sum-rate expression of the channel error. Simulation results show that compared with the robust minimum interference leakage algorithm, when the SNR is 10 dB and the channel error variance value is 0.05, the spectrum efficiency of the system is increased by 25% and the energy efficiency is increased by 38%. Therefore, the proposed algorithm can effectively improve system performance at low SNR.

Key words: wireless communication, channel error, robust interference alignment, low Signal-To-Noise Ratio (SNR), system sum rate

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