大规模MIMO天线选择关键技术研究

发布时间：2018-06-04 09:46

本文选题：大规模MIMO + 天线选择　；参考：《北京交通大学》2017年硕士论文

【摘要】：随着无线通信技术的发展和移动智能终端的普及,传统MIMO(Multiple-Input Multiple-Output)技术已经难以支持日益增长的无线数据流量需求。大规模MIMO(Massive Multiple-Input Multiple-Output)作为传统MIMO技术的扩展和演进,在不增加发射功率和不拓展带宽的前提下,通过部署大量的天线,充分挖掘空间维度资源,能够提供相当大的复用和分集增益,从而显著提升频谱效率和信道容量。传统的MIMO技术要求配备与天线数等量的射频链路,由于大规模MIMO系统中天线众多,如果按照传统的方式进行配置,将使得系统硬件成本以及系统复杂度大幅度上升。与此同时,增加的射频链路会导致射频功耗的提高,不利于实现能量效率优先的绿色通信。天线选择技术能够在不影响大规模MIMO技术优势的前提下,显著降低射频成本和系统复杂度,并且优化系统的能量效率。因此,本文对大规模MIMO中的天线选择技术进行了分析和研究。论文的主要内容如下:论文首先阐述了大规模MIMO自身的优势与面临的挑战,通过对天线选择技术的研究现状和经典的天线选择算法的分析和介绍,阐明了天线选择技术对于大规模MIMO系统的必要性。针对大规模MIMO的特点,在信道容量最大化的准则下,提出了相应的解决方案。双向搜索天线选择算法能够灵活应对不同的选择天线数需求,并保持较低的计算复杂度;基于矩阵体积的改进Maxvol天线选择算法可以实现全局优化的快速天线子集选择,同时改善了低信噪比情况的性能;新型低复杂度的收发联合天线选择算法可以达到与单侧天线选择计算复杂度相当的快速联合天线选择,通过仿真验证了上述算法的有效性。针对天线选择技术在大规模MIMO能量效率优化方面的作用进行了研究。首先根据大规模MIMO系统的特性,推导了多用户大规模MIMO的和容量表达式,分析单用户大规模MIMO系统天线选择与能量效率优化之间的关系,进而扩展到多用户场景,建立了多用户大规模MIMO天线选择能量效率模型,讨论了能量效率与选择天线数量之间的关系,通过数学推导证明了使得系统能量效率最大化的最优天线数的存在性与唯一性,并在此基础上提出了基于二分查找的天线选择算法,在最优天线数确定后,能量效率优化问题转化为容量优化问题。仿真结果表明,针对大规模MIMO系统,天线选择技术具有显著提高系统能量效率的作用,对于实现绿色通信具有重要价值。
[Abstract]:With the development of wireless communication technology and the popularity of mobile intelligent terminals, the traditional MIMO(Multiple-Input Multiple-Output technology has been difficult to support the increasing demand for wireless data traffic. Large-scale MIMO(Massive Multiple-Input Multiple-Output, as an extension and evolution of traditional MIMO technology, can provide considerable multiplexing and diversity gain by deploying a large number of antennas and fully mining spatial dimension resources without increasing transmission power and bandwidth. Thus, spectrum efficiency and channel capacity are significantly improved. The traditional MIMO technology requires RF links equal to the number of antennas. Because of the large number of antennas in large scale MIMO systems, the hardware cost and complexity of the system will be greatly increased if the system is configured in the traditional way. At the same time, the increase of RF link will lead to the increase of RF power consumption, which is not conducive to the realization of energy efficiency priority green communication. Antenna selection technology can significantly reduce the RF cost and system complexity without affecting the advantages of large-scale MIMO technology and optimize the energy efficiency of the system. Therefore, the antenna selection technique in large-scale MIMO is analyzed and studied in this paper. The main contents of this paper are as follows: firstly, the advantages and challenges of large-scale MIMO are described, and the research status of antenna selection technology and the analysis and introduction of classical antenna selection algorithm are introduced. The necessity of antenna selection for large scale MIMO systems is expounded. According to the characteristics of large scale MIMO, a corresponding solution is proposed under the criterion of maximization of channel capacity. Two-way search antenna selection algorithm can flexibly respond to different antenna selection requirements and maintain low computational complexity. Improved Maxvol antenna selection algorithm based on matrix volume can achieve global optimization of fast antenna subset selection. At the same time, the performance of low SNR is improved. A new low complexity antenna selection algorithm can achieve fast antenna selection with the same computational complexity as single side antenna selection. The simulation results show that the algorithm is effective. The effect of antenna selection technology on energy efficiency optimization of large scale MIMO is studied. Firstly, according to the characteristics of large-scale MIMO system, the sum capacity expression of multi-user large-scale MIMO is derived, and the relationship between antenna selection and energy efficiency optimization of single-user large-scale MIMO system is analyzed, which is extended to multi-user scenarios. A multi-user large-scale MIMO antenna selection energy efficiency model is established, and the relationship between energy efficiency and the number of selected antennas is discussed. The existence and uniqueness of the optimal number of antennas that maximize the energy efficiency of the system are proved by mathematical derivation. On this basis, an antenna selection algorithm based on binary search is proposed. After the optimal number of antennas is determined, the energy efficiency optimization problem is transformed into the capacity optimization problem. The simulation results show that antenna selection technology can significantly improve the energy efficiency of large scale MIMO systems and is of great value to the realization of green communication.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN919.3

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