北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2018, Vol. 41 ›› Issue (4): 63-68.doi: 10.13190/j.jbupt.2017-248

• 论文 • 上一篇    下一篇

大规模MIMO系统中基于WMMSE的混合预编码算法

魏敏1, 汤文杰1, 滕颖蕾1, 陈广泉2, 宋梅1   

  1. 1. 北京邮电大学 北京市安全生产智能监控重点实验室, 北京 100876;
    2. 联通在线信息科技有限公司, 北京 100032
  • 收稿日期:2017-12-07 出版日期:2018-08-28 发布日期:2018-10-09
  • 作者简介:魏敏(1994-),女,硕士生,E-mail:weimin2016140309@bupt.edu.cn;滕颖蕾(1983-),女,副教授,博士生导师.
  • 基金资助:
    国家自然科学基金项目(61427801);北京市自然科学基金项目(L171011)

A Hybrid Precoding Algorithm Based on Weighted Minimum Mean Square Error in Massive MIMO Systems

WEI Min1, TANG Wen-jie1, TENG Ying-lei1, CHEN Guang-quan2, SONG Mei1   

  1. 1. Beijing Key Laboratory of Work Safety Intelligent Monitoring, Beijing University of Posts and Telecommunications, Beijing 100876, China;
    2. China Unicom Online Information Technology Company, Beijing 100032, China
  • Received:2017-12-07 Online:2018-08-28 Published:2018-10-09

摘要: 为提高大规模多输入多输出(MIMO)系统复用增益,降低天线硬件成本,提出一种基于全阵列天线结构的混合预编码算法.以多用户加权最小均方误差为优化目标,综合考虑天线结构硬件限制、用户公平性和功率限制,采用数字—模拟混合式两级预编码与最优一级数字预编码最大逼近的方法求解两级混合预编码.仿真结果表明,所提算法能最大限度地减小所求混合预编码矩阵与最优一级预编码矩阵的误差,具有较好的收敛性,可获得近乎最优的混合预编码性能增益.

关键词: 大规模多输入多输出, 全阵列天线结构, 混合预编码, 加权最小均方误差

Abstract: To improve the multiplexing gain and reduce the hardware cost of antennas in massive multiple-input multiple-output systems, a hybrid precoding algorithm based on the fully-connected antenna structure was proposed. Aiming at minimizing the multiuser weighted minimum mean square error, an optimization problem was established under the constraints of antenna structure, user fairness and the limitation of power and the hybrid precoding problem was solved by utilizing the best approaching to the digital precoding. Simulations verify that the proposed algorithm narrows down the gap between the hybrid precoder and the optimal one-stage precoder to the greatest extent with a good convergence and obtains a near-optimal solution with significant gain.

Key words: massive multiple-input multiple-output, fully-connected antenna structure, hybrid precoding, weighted minimum mean square error

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