通信学报 ›› 2019, Vol. 40 ›› Issue (10): 169-179.doi: 10.11959/j.issn.1000-436x.2019174

• 学术通信 • 上一篇    下一篇

基于能效的渐近式RZF协作波束成形算法研究

张颖慧, 张彪, 逯效亭, 刘洋   

  1. 内蒙古大学电子信息工程学院,内蒙古 呼和浩特 010021
  • 修回日期:2019-07-23 出版日期:2019-10-25 发布日期:2019-11-07
  • 作者简介:张颖慧(1982- ),女,内蒙古通辽人,博士,内蒙古大学副教授,主要研究方向为绿色通信、信号处理。|张彪(1995- ),男,内蒙古乌兰察布人,内蒙古大学硕士生,主要研究方向为 5G通信。|逯效亭(1994- ),男,内蒙古包头人,内蒙古大学硕士生,主要研究方向为 5G通信。|刘洋(1981- ),男,满族,内蒙古通辽人,博士,内蒙古大学教授,主要研究方向为无线通信、物联网。
  • 基金资助:
    国家自然科学基金资助项目(61761033);内蒙古自然科学基金资助项目(2016MS0604)

Asymptotic RZF cooperative beamforming algorithm based on energy efficiency

Yinghui ZHANG, Biao ZHANG, Xiaoting LU, Yang LIU   

  1. College of Electronic Information Engineering,Inner Mongolia University,Hohhot 010021,China
  • Revised:2019-07-23 Online:2019-10-25 Published:2019-11-07
  • Supported by:
    The National Natural Science Foundation of China(61761033);The Natural Science Foundation of Inner Mongolia Autonomous Region of China(2016MS0604)

摘要:

在下行异构大规模MIMO系统中,针对目前多流正则化迫零波束成形算法将正则化项中的每根天线功率约束值均设为固定的上限,且忽略在实际部署环境中天线数量、用户数以及QoS等因素影响,设计的Multiflow-RZF波束成形并不能获得最佳能效的问题,提出一种低复杂度的渐进式RZF协作波束成形算法。该算法在每次迭代中,对天线功率约束集合进行最优选择,渐近地获得最优波束成形设计以平衡用户间的干扰,在满足QoS约束和天线功率约束下,考虑天线数量、用户数等因素的影响,实现异构大规模MIMO系统能效最优。鉴于回程功耗在大规模MIMO系统中的重要性,进一步考虑更符合实际应用的回程功耗系统模型,分析了回程功耗对系统性能的影响。分析和仿真结果表明,提出的新算法具有较强的实用性和较大的性能提升,特别是当天线数较大时,算法性能接近最优,特别适合于下一代通信的大规模 MIMO系统。

关键词: 能效, 功率约束, 正则化迫零, 大规模MIMO, 异构网

Abstract:

A low complexity asymptotic regularized zero forcing cooperative beamforming algorithm based on energy efficiency in heterogeneous massive MIMO system was proposed,aiming at the problem that the current multi-flow regularization zero forcing beamforming algorithm sets the power constraint of each antenna in the regularization term as a fixed value and ignores the influences of factors such as the number of antennas,the number of users and QoS.The algorithm selects the optimal antenna power constraint set through the optimization method,and the optimal beamforming was asymptotically ob-tained to balance the interference among users to achieve the optimal energy efficiency,considering the impact of the number of antennas and users with the constraints of the antenna power and QoS.In view of the importance of backhaul in massive MIMO system,a backhaul power consumption model and the impact of backhaul power consumption on system performance was analyzed.Analysis and simulation results show that the proposed algorithm has great improvement of the performance,especially when the number of antennas is large.The algorithm is close to optimal performance,especially suitable for massive MIMO system of next generation communication.

Key words: energy efficiency, power constraint, regularized zero-forcing, Massive MIMO, heterogeneous network

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