多用户MIMO广播信道波束赋形与能效分析

发布时间：2019-04-30 14:16

【摘要】：伴随着无线移动通信技术的快速发展,人们对能够进行及时可靠的移动通信需求愈加显著。而有限的频谱资源、能量资源又制约着这一诉求,因此,不断提高频谱利用效率和能量利用效率显得愈加迫切。波束赋形技术在提升MIMO无线通信系统容量、抑制干扰,进而提升系统频谱效率方面有着重要的促进作用。目前,该技术已经被写入3GPP协议。波束赋形技术通过对发射信号和接收信号进行必要的处理,使得信干噪比显著增加,以此提升系统容量和抑制干扰。这种技术也可以看做是对发送信号的空间滤波：通过在发射端设计发射矩阵,使得信号在尽可能的对准期望用户的前提下,再尽可能的减少对其它用户的干扰；通过在接收端设计接收矩阵,使得尽可能的提升期望信号功率,同时抑制干扰信号功率。在完成波束赋形矩阵设计后,对功率进行合理有效的分配也是提升系统频效和能效的关键技术之一。一方面,提升发射信号功率,可以有效的提高系统容量,但是在发射信号功率增加到一定程度后,频谱效率和能量效率不会再随着功率的提升而增加。另一方面,本着节能减排的思想,系统功耗当然是越小越好。结合波束赋形技术,在此基础上研究系统能量效率,设计合理的功率分配协方差矩阵以期提高系统能量效率,这是值得研究和分析的。在设计接收端和发射端的波束赋形矩阵时,完整的信道信息对其性能有着极其重要的作用。但是在实际通信系统中,获取完整的信道信息比较困难,因此,如何在不完整信道信息情况下设计波束赋形矩阵也是值得研究的。本文针对多用户MIMO技术中的波束赋形技术,能效优化方面的问题进行了如下研究：第一章介绍本文研究的意义、广播信道下的多用户MIMO波束赋形技术以及能量效率的研究现状。第二章介绍波束赋形技术、能量效率优化的常见研究方式方法,介绍本文所需的数学优化理论,建立系统传输模型、功耗模型等等。第三章提出了两种新的波束赋形算法,分别是基于信号空间维度波束赋形算法和基于空间距离波束赋形算法。针对这两种算法,我们给了发射端和接收端波束赋形矩阵的闭式解,并且结合波束赋形算法,分析了能效优化的功率分配。最后给出了仿真分析。第四章研究分析了信道信息不完整情况下的基于空间距离和基于信号空间维度算法的波束赋形矩阵设计,以及对能量效率的影响。第五章总结全文,简述下一步研究工作
[Abstract]:With the rapid development of wireless mobile communication technology, the demand for timely and reliable mobile communication becomes more and more obvious. The limited spectrum resources and energy resources restrict this demand, therefore, it is more and more urgent to improve the spectrum utilization efficiency and energy utilization efficiency. Beamforming technology plays an important role in improving the capacity of MIMO wireless communication system, suppressing interference and improving the spectrum efficiency of the system. At present, the technology has been written to the 3GPP protocol. The beamforming technique can increase the signal-to-noise ratio (SNR) by processing the transmitted signal and the received signal, so as to improve the system capacity and suppress the interference. This technology can also be regarded as spatial filtering of the transmitted signal: by designing the transmitting matrix at the transmitting end, the signal can aim at the desired user as much as possible, and then reduce the interference to other users as much as possible; By designing a reception matrix at the receiver, the desired signal power is increased as much as possible, while the interference signal power is suppressed. After the design of beamforming matrix, reasonable and efficient power allocation is also one of the key technologies to improve the frequency and energy efficiency of the system. On the one hand, increasing the transmission signal power can effectively improve the system capacity, but when the transmission signal power increases to a certain extent, the spectrum efficiency and energy efficiency will no longer increase with the increase of the power. On the other hand, in line with the idea of energy saving and emission reduction, the system power consumption is of course the smaller the better. Combined with beamforming technology, the energy efficiency of the system is studied and the reasonable power allocation covariance matrix is designed to improve the energy efficiency of the system, which is worthy of study and analysis. When designing the beamforming matrix of receiver and transmitter, the complete channel information plays an important role in its performance. However, in practical communication systems, it is difficult to obtain complete channel information. Therefore, how to design the beamforming matrix in the case of incomplete channel information is also worth studying. In this paper, the problems of beam forming and energy efficiency optimization in multi-user MIMO technology are studied as follows: in the first chapter, the significance of this research, the research status of multi-user MIMO beamforming technology and energy efficiency in broadcast channel are introduced. The second chapter introduces the beam-forming technology, the common research methods of energy efficiency optimization, introduces the mathematical optimization theory needed in this paper, establishes the system transmission model, power consumption model and so on. In chapter 3, two new beamforming algorithms are proposed, one is based on spatial dimension beamforming algorithm, and the other is based on spatial distance beamforming algorithm. For these two algorithms, we give the closed-form solution of the beamforming matrix at the transmitter and receiver, and analyze the power allocation of energy efficiency optimization by combining the beamforming algorithm. Finally, the simulation analysis is given. In chapter 4, the design of beamforming matrix based on spatial distance and signal spatial dimension algorithm with incomplete channel information is studied and analyzed, and the influence on energy efficiency is also analyzed. Chapter V summarizes the full text, briefly describes the next step of the research work.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN929.5

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