大规模MIMO定位关键技术研究

发布时间：2018-12-28 07:09

【摘要】：多输入多输出(Multiple Input Multiple Output,MIMO)技术是无线蜂窝通信系统的关键技术。随着无线蜂窝网络系统的发展,手机用户数量也快速增长,无线定位技术也变得越来越不可缺少。而未来第五代通信系统(FifthGeneration,5G)即将普及应用,大规模MIMO基站配备有天线数量巨大的天线阵列,合理利用天线阵列接收信号参数对用户进行三维空间定位不仅可以为用户提供位置信息,还能够为移动中的用户提供功率控制和越区切换。首先,本文对大规模MIMO技术以及无线定位技术的背景、国内外研究现状以及面临的问题进行了概述,并将这两种技术融合,引出了本文的主要研究内容,即大规模MIMO定位技术。其次,本文介绍了无线定位技术常用的定位算法并分析其各自优缺点。随后探讨分析无线定位技术面临的主要问题及现有解决方案,并介绍了无线定位技术中常用的定位性能判定标准。基于以上基础知识本文最终选定多参数联合定位技术为适合本文环境背景的定位算法。再次,本文介绍了到达角(Direction of Arrival,DOA)估计技术的传统算法,对多重信号分类(Multiple Signal Classification,MUSIC)算法以及旋转不变子空间(Estimation of Signal Parameters via Rotational Invariance Techniques,ESPRIT)算法进行比较,并选定ESPRIT算法为大规模MIMO系统所采用的DOA估计算法。随后介绍了矩形天线阵列适用的二维DOA估计算法,并提出一种改进算法,该算法在方形阵列下具有最佳估计性能。最后,本文分析了最小二乘联合定位法和基于最大似然估计的参数重构定位法的不足,将最小二乘法推广到三维定位,并提出一种非视距(None-LineofSight,NLOS)环境下的基于传输模型的多信号参数约束联合定位方法。该方法首先对接收的多径信号进行预处理得到每个基站的信号参数,再通过传输模型得到约束不等式组,最终采用求解无约束非线性最小二乘问题的方法进行三维空间位置估计,仿真结果表明该算法能够有效地减弱NLOS环境下定位误差。
[Abstract]:Multi-input multi-output (Multiple Input Multiple Output,MIMO) technology is a key technology in wireless cellular communication systems. With the development of wireless cellular network system, the number of mobile phone users is growing rapidly, and wireless positioning technology is becoming more and more indispensable. In the future, the fifth generation communication system (FifthGeneration,5G) will soon be widely used. Large scale MIMO base stations will be equipped with antenna arrays with a large number of antennas. The reasonable use of antenna array receiving signal parameters to locate users in 3D space can not only provide location information for users, but also provide power control and handoff for mobile users. First of all, the background of large-scale MIMO technology and wireless positioning technology, domestic and foreign research status and problems are summarized, and the fusion of these two technologies leads to the main research content of this paper, that is, large-scale MIMO positioning technology. Secondly, this paper introduces the commonly used localization algorithms of wireless location technology and analyzes their respective advantages and disadvantages. Then, the main problems and existing solutions of wireless positioning technology are analyzed, and the commonly used positioning performance criteria are introduced. Based on the above basic knowledge, this paper finally selects the multi-parameter joint location technology as the location algorithm suitable for the background of this paper. Thirdly, this paper introduces the traditional algorithms of angle of arrival (Direction of Arrival,DOA) estimation, compares the multi-signal classification (Multiple Signal Classification,MUSIC algorithm and the rotation-invariant subspace (Estimation of Signal Parameters via Rotational Invariance Techniques,ESPRIT algorithm. ESPRIT algorithm is selected as the DOA estimation algorithm for large scale MIMO system. Then, a two-dimensional DOA estimation algorithm for rectangular antenna arrays is introduced, and an improved algorithm is proposed, which has the best estimation performance under square arrays. Finally, this paper analyzes the shortcomings of the least squares combined localization method and the parameter reconstruction localization method based on maximum likelihood estimation. The least square method is extended to 3D location, and a non-line-of-sight (None-LineofSight,) method is proposed. NLOS) based multi-signal parameter constrained joint localization method based on transmission model. In this method, the received multipath signal is preprocessed to obtain the signal parameters of each base station, and then the constrained inequality set is obtained by transmission model. Finally, an unconstrained nonlinear least square method is used to estimate the position in three dimensional space. The simulation results show that the algorithm can effectively reduce the location error in NLOS environment.
【学位授予单位】：东南大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN919.3

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