基于波束成形的Massive MIMO导频污染抑制算法研究

发布时间：2018-04-18 15:28

本文选题：Massive + MIMO系统　；参考：《北京交通大学》2017年硕士论文

【摘要】：Massive MIMO(multiple-input multiple output)技术在基站侧部署大量天线,可以在同一时频资源上同时服务大量用户,不仅可以提高系统速率和可靠性,还可以降低基站发射功率,成为5G候选技术之一。Massive MIMO优势的实现依赖于准确的信道状态信息(channel statement information,CSI)。FDD(Frequency division duplex)模式下,CSI的获得依赖用户反馈,参考信号和用户反馈的开销随着天线数目增加而不可接受。因而通常将Massive MIMO技术用于TDD(time-division duplex)模式,利用信道的互易性,根据用户发送的上行导频来做信道估计,获得CSI。真实系统中,导频长度有限,小区间共用一套导频,不同小区用户发来的非正交导频造成导频污染。导频污染严重制约了 Massive MIMO系统的性能。如何抑制导频污染成为Massive MIMO系统亟待解决的问题。本文首先研究了线状蜂窝网络中的导频污染,分析了系统的信道估计误差和频谱效率以及影响导频污染的多种因素,包括天线数量、小区数量、导频长度、交叉增益等。在研究面状蜂窝网络时,充分借鉴了线状蜂窝网络的结论。面状蜂窝网络中,小区数目较多,小区间共用同一套正交导频时,导频污染严重。针对这一现状,本文从降低干扰和增强有用信号两个方面寻找解决Massive MIMO系统中的导频污染问题的方法。在降低干扰方面,对比了两种常用导频污染抑制算法:时隙偏移法和导频功率控制法。研究表明这两种方法都可以将交叉增益较大、干扰较强的小区用户发送导频的时隙与目标小区用户发送导频时隙错开,在时域提供导频正交性,抑制导频污染。但在时隙偏移法中,消除导频污染的同时引入了相邻小区的数据干扰。而且需要频繁修改帧结构,不灵活,实用性低。相比而言,导频功率控制算法不会引入其他干扰,而且只需要缩短导频长度就可以实现,简单实用。在增强有用信号方面,各小区基站采用低复杂度的混合模拟/数字波束赋形结构。在模拟域,基站产生一系列不同方向的模拟波束,用户通过测量选择最佳模拟波束接入。显然,模拟波束的设计和选择关系到信道估计的准确性和导频接收质量。本文详细设计了模拟域波束的分布模型、波束集合、最佳波束的搜索等。并提出了基于角度和幅度的插值优化算法。插值算法基于模拟波束之间的空间相关性,在插值算法中,基站可以动态调整模拟波束,令波束更好地对准用户,增强目标导频的接收质量,进一步降低导频污染,提升系统性能。对解决Massive MIMO系统中导频污染问题有一定的理论价值和实践意义。
[Abstract]:Massive MIMO(multiple-input multiple output (Massive MIMO(multiple-input multiple output) technology deploys a large number of antennas on the base station side, which can simultaneously serve a large number of users on the same time-frequency resource. It can not only improve the system speed and reliability, but also reduce the base station transmission power.As one of the 5G candidate technologies, the realization of passive MIMO advantage depends on the accurate channel statement information channel statement information CSI, FDD frequency division duplexe mode. The cost of reference signal and user feedback is unacceptable with the increase of the number of antennas.Therefore, the Massive MIMO technology is usually used in the TDD(time-division duplex mode. The channel estimation is based on the uplink pilot sent by the user and the CSI is obtained by using the reciprocity of the channel.In the real system, the pilot length is limited, and a set of pilots is shared in each cell, and the non-orthogonal pilots sent by different cell users cause pilot pollution.Pilot pollution seriously restricts the performance of Massive MIMO system.How to suppress pilot pollution has become an urgent problem in Massive MIMO system.In this paper, pilot pollution in linear cellular networks is studied firstly. The channel estimation error and spectral efficiency of the system are analyzed, as well as various factors affecting pilot pollution, including the number of antennas, the number of cells, pilot length, cross-gain and so on.In the study of planar cellular networks, the conclusion of linear cellular networks is fully used for reference.In planar cellular networks, the number of cells is large, and the pilot pollution is serious when the cells share the same set of orthogonal pilots.In view of this situation, this paper looks for ways to solve the pilot pollution problem in Massive MIMO system from the aspects of reducing interference and enhancing useful signals.In the aspect of reducing interference, two common pilot pollution suppression algorithms are compared: slot offset method and pilot power control method.The results show that both of the two methods can stagger the pilot time slots of the cell users with large cross-gain and strong interference with the target cell users to provide pilot orthogonality in time domain and suppress pilot pollution.However, in the time slot migration method, the data interference of adjacent cells is introduced while the pilot pollution is eliminated.Moreover, the frame structure needs to be modified frequently, which is inflexible and low practicability.In contrast, the pilot power control algorithm does not introduce other interference, and only need to shorten the pilot length can be achieved, simple and practical.In the aspect of enhancing useful signals, each cell base station adopts a low complexity hybrid analog / digital beamforming structure.In analog domain, the base station generates a series of analog beams in different directions, and users choose the best analog beam access through measurement.It is obvious that the design and selection of analog beam is related to the accuracy of channel estimation and the quality of pilot reception.In this paper, the beam distribution model, beam set and optimal beam search are designed in detail.An interpolation optimization algorithm based on angle and amplitude is proposed.The interpolation algorithm is based on the spatial correlation between the analog beams. In the interpolation algorithm, the base station can dynamically adjust the analog beam, make the beam better aimed at the user, enhance the receiving quality of the target pilot, and further reduce the pilot pollution.Improve system performance.It has certain theoretical value and practical significance to solve pilot pollution problem in Massive MIMO system.
【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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