基于分布式MIMO系统的天线选择算法的研究

发布时间：2018-05-13 15:08

本文选题：分布式MIMO + 信道容量　；参考：《南京邮电大学》2017年硕士论文

【摘要】：通信技术的出现,改变了人们的生活。随着社会的进步和通信技术的迅猛发展,通信业务也逐渐走向多元化,从传统的话音通信逐步发展成为如今的多媒体通信,人们对通信质量的要求越来越高,这对移动通信提出了更高的要求。如何在有限的频谱资源条件下,提高信道容量和信息传输速率,增大频谱利用率,成为人们研究的焦点问题。MIMO技术的诞生,为解决这一问题提供了新的研究方向。多输入多输出(Multiple Input Multiple Output,MIMO)技术指在发射端和接收端分别使用多个发射天线和多个接收天线进行信息的发送和接收,从而改善通信质量。MIMO技术能够充分地利用空间资源,在不增加频谱和天线发射功率的前提下,可以成倍地提高系统的信道容量,显示出明显的优势。分布式天线系统是未来无线通信的开放式架构系统,具有覆盖均匀、减少盲区等优点。分布式MIMO系统是将MIMO技术和分布式天线技术相结合的产物。与集中式MIMO系统相比,分布式MIMO系统具有更大的平均信道容量,更低的发射功率,更低的系统部署费用等优势。但是MIMO系统和分布式MIMO系统由于多天线的应用,射频链路也会相应地增加,最终会导致系统复杂度的增加和硬件成本的提高。天线选择技术被认为是一种能够有效降低系统的成本和复杂度的有效方法。天线选择的准则主要有两种,分别为信道容量最大准则和接收误码率最小准则。本文主要基于分布式MIMO系统对天线选择算法进行相应的研究,以最大化系统容量和降低复杂度为目标。论文首先从MIMO系统入手,研究MIMO系统的传输模型,并推导出MIMO系统的信道容量。其次从MIMO系统的信道容量推导出分布式MIMO系统的信道容量,并对分布式MIMO系统容量和集中式MIMO系统容量进行仿真分析和比较,说明分布式MIMO系统比集中式MIMO系统具有更高的系统容量和更均匀的覆盖率等优势。然后对MIMO系统的几种经典的天线选择算法进行对比分析,并将这几种经典天线选择算法应用于分布式MIMO系统中进行仿真分析,证明应用天线选择技术可以效地降低系统的复杂度。最后,本文基于经典算法的核心思想给出了两种以端口选择为基础的天线选择算法,并与经典算法进行仿真对比。仿真结果表明:新算法能够有效地降低系统的复杂度,与最优算法相比,只有极小的信道容量损失,明显地降低了天线选择所耗费的时间。
[Abstract]:The advent of communication technology has changed people's lives. With the development of the society and the rapid development of communication technology, the communication business is becoming more and more diversified, from the traditional voice communication to the multimedia communication. This puts forward higher requirements for mobile communications. How to improve the channel capacity and the rate of information transmission and increase the spectrum efficiency under the condition of limited spectrum resources has become the focus of research. MIMO technology has provided a new research direction for solving this problem. Multiple-output Input Multiple output Mimo (Mimo) technology refers to the use of multiple transmit antennas and multiple receiving antennas to transmit and receive information at the transmitter and receiver, respectively, so as to improve the communication quality. MIMO technology can make full use of space resources. Without increasing the frequency spectrum and antenna transmitting power, the channel capacity of the system can be increased exponentially, showing obvious advantages. Distributed antenna system is an open architecture system for wireless communication in the future. It has the advantages of uniform coverage and less blind area. Distributed MIMO system is a combination of MIMO technology and distributed antenna technology. Compared with the centralized MIMO system, the distributed MIMO system has the advantages of larger average channel capacity, lower transmit power and lower system deployment cost. However, because of the application of multiple antennas in MIMO system and distributed MIMO system, the RF link will increase correspondingly, which will eventually lead to the increase of system complexity and the increase of hardware cost. Antenna selection is considered to be an effective method to reduce the cost and complexity of the system. There are two main criteria for antenna selection, one is the maximum channel capacity criterion and the other is the minimum bit error rate criterion. In this paper, the antenna selection algorithm based on distributed MIMO system is studied in order to maximize the system capacity and reduce the complexity. Firstly, the transmission model of MIMO system is studied from MIMO system, and the channel capacity of MIMO system is deduced. Secondly, the channel capacity of distributed MIMO system is deduced from the channel capacity of MIMO system, and the simulation analysis and comparison of distributed MIMO system capacity and centralized MIMO system capacity are carried out. It shows that distributed MIMO system has higher system capacity and more uniform coverage than centralized MIMO system. Then several classical antenna selection algorithms of MIMO system are compared and analyzed, and these classical antenna selection algorithms are applied to distributed MIMO system for simulation analysis. It is proved that using antenna selection technique can effectively reduce the complexity of the system. Finally, based on the core idea of classical algorithms, two antenna selection algorithms based on port selection are presented and compared with the classical algorithms. Simulation results show that the new algorithm can effectively reduce the complexity of the system, compared with the optimal algorithm, there is only a minimal loss of channel capacity, which significantly reduces the time spent in antenna selection.
【学位授予单位】：南京邮电大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN919.3

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