基于压缩感知的MIMO通信系统用户接入管理研究

发布时间：2018-11-25 10:04

【摘要】：近年来,无线通信和网络技术迅猛发展,多媒体移动通信等新业务也更加多样化,频谱资源也随之日益紧张。为了解决人们持续增长的无线通信业务需求与有限通信容量之间的矛盾,无线宽带移动通信己由传统的单输入单输出(Single-input Single-output, SISO)系统发展到多输入多输出(Multiple-input Multiple-output, MIMO)系统。多天线系统中多用户接入需要估计用户的信道状况信息,近年来新发展起来的压缩感知理论能够在有效获得信道估计的前提下,大大增加信道资源利用率,提高用户接入和信道估计的性能和效果。论文首先全面介绍了压缩感知的基本理论,同时描述了压缩感知在无线通信网络中的应用现状,探讨了贝叶斯压缩感知等新型压缩感知基本理论,分析了其关键技术、应用方向和应用现状。本文主要研究基于压缩感知原理的多天线系统中用户接入管理和信道估计研究,该方法充分利用系统中接入用户的稀疏性和无线信道的稀疏性,在相同身份序列的条件下,实现更高精度的用户检测和信道估计,同时提高了信道资源的利用率。设计了一种基于网络中终端数目变化而自适应调整身份序列长度的方法,该方法可以随着用户量的变化而适当减少或者增加。相比于固定长度的做法,当用户量变少时,该方法可以适时减少序列长度,降低信道资源的浪费和终端能量的消耗等等。此外,为了更好的提高检测效率,增强信道资源的利用率,减少基站和终端的能量消耗,论文又提出了基于哈达玛矩阵方法构造身份序列的方法,在保证信道估计表现的同时,更进一步缩短了所需身份序列的长度,在能量表现上有一定的提高。论文的最后探讨了下一步的研究思路。
[Abstract]:In recent years, with the rapid development of wireless communication and network technology, multimedia mobile communication and other new services have become more diversified, and the spectrum resources have become increasingly tight. In order to solve the contradiction between the increasing demand of wireless communication service and the limited communication capacity, the traditional single input single output (Single-input Single-output,) has been used in wireless wideband mobile communication. SISO) system is developed to multi-input multi-output (Multiple-input Multiple-output, MIMO) system. In multi-antenna systems, multi-user access needs to estimate the channel status information of users. In recent years, the newly developed compressed sensing theory can greatly increase the utilization of channel resources on the premise of effective channel estimation. Improve the performance and effect of user access and channel estimation. In this paper, the basic theory of compression sensing is introduced, and the application status of compression sensing in wireless communication network is described. The basic theory of new compression sensing, such as Bayesian compression perception, is discussed, and the key technology is analyzed. Application direction and status quo. This paper focuses on the research of user access management and channel estimation in multi-antenna systems based on compressed sensing theory. This method makes full use of the sparsity of access users in the system and the sparsity of wireless channels under the condition of the same identity sequence. Higher accuracy of user detection and channel estimation is achieved, and the utilization of channel resources is improved. An adaptive method of adjusting the length of identity sequence based on the number of terminals in the network is designed. The method can be reduced or increased with the change of the number of users. Compared with the fixed length method, when the number of users becomes smaller, the method can reduce the length of the sequence, reduce the waste of channel resources and the consumption of terminal energy and so on. In addition, in order to improve the detection efficiency, enhance the utilization of channel resources and reduce the energy consumption of base stations and terminals, this paper proposes a method of constructing identity sequences based on Hadamard matrix method, which ensures the performance of channel estimation at the same time. The length of the required identity sequence is further shortened, and the energy performance is improved. Finally, the paper discusses the next research ideas.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN919.3

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