基于消息传递算法的小区间干扰抑制技术研究

发布时间：2018-03-26 16:26

本文选题：小区间干扰　切入点：基站协作　出处：《郑州大学》2017年硕士论文

【摘要】：在通信网络中以较高的频率复用因子密集部署基站,能够充分利用稀缺的频谱资源并大幅度提高单位面积的系统容量。然而基站密集部署环境下,会产生更加严重的小区间干扰(Inter-Cell Interference,ICI),影响小区边缘用户的通信质量。因此,未来通信网络中亟待寻找高效率的ICI抑制方案。基站协作技术的产生为抑制ICI提供了新的思路,通过多小区协作处理能够在很大程度上抑制干扰的影响。集中式协作对回程容量的要求很高,而分布式协作则以较低的系统开销得到了更加广泛的应用。考虑到基于因子图模型的消息传递算法在用于信号估计和分布式计算时具有良好特性,本文将基于因子图模型的消息传递算法应用到多小区基站协作系统中来抑制ICI,取得了良好的效果。论文主要研究内容如下:1、论文研究了ICI的产生机理以及基站协作下的ICI抑制技术,描述了基于因子图模型的消息传递算法,重点给出了置信传播(Belief Propagation,BP)以及变分消息传递(Variational Message Passing,VMP)更新准则下的消息计算公式。2、针对上行链路基站多天线系统中存在的ICI问题,研究了多小区通信环境下接收机协作分布式迭代干扰抑制算法。首先概述了迭代接收机技术的基本理论及其潜在优势,为协作迭代接收机的设计奠定了基础;然后对系统进行因子图建模,通过因式分解建立基站多天线系统协作接收机相对应的因子图模型,推导了因子图模型中节点之间的消息计算公式,通过在接收机间进行信息交互,设计实现了上行链路接收机协作分布式迭代干扰抑制算法。3、在下行链路基站协作系统中,设计实现了基于广义近似消息传递的分布式广义迫零编码算法。首先研究了多用户系统中的部分预编码算法,其中广义迫零预编码在复杂度和性能上取得了较好的折中,将其用于集中式协作系统在基站端进行联合预编码能够有效抑制ICI;然而集中式协作预编码的实现受到复杂度的限制和有限回程容量的制约,因此,本文提出了基于广义近似消息传递的分布式广义迫零预编码算法。
[Abstract]:Dense deployment of base stations with high frequency multiplexing factor in communication networks can make full use of scarce spectrum resources and greatly improve the system capacity per unit area. It will produce more serious inter-cell interference and affect the communication quality of the cell edge users. Therefore, it is urgent to find a high efficiency ICI suppression scheme in the future communication network. The generation of base station cooperation technology provides a new way to suppress ICI. Through multi-cell cooperative processing, the influence of interference can be restrained to a large extent. Distributed collaboration is widely used with low system overhead, considering that the message passing algorithm based on factor graph model has good characteristics in signal estimation and distributed computing. In this paper, the message passing algorithm based on factor graph model is applied to the multi-cell base station cooperation system, and good results are obtained. The main contents of this paper are as follows: 1. The generation mechanism of ICI and the base station cooperation are studied in this paper. For ICI suppression, This paper describes the message passing algorithm based on factor graph model, and gives the message calculation formula .2under the confidence Propagation BPs and the variational Message Passinging-VMPs update criterion, aiming at the ICI problem in uplink base station multi-antenna system. In this paper, the cooperative distributed iterative interference suppression algorithm in multi-cell communication environment is studied. Firstly, the basic theory and potential advantages of iterative receiver technology are summarized, which lays a foundation for the design of cooperative iterative receiver. Then the factor graph model of the system is built by factorization, and the corresponding factor graph model of the cooperative receiver of the base station multi-antenna system is established, and the calculation formula of messages between nodes in the factor graph model is derived. By exchanging information between receivers, an uplink receiver cooperative distributed iterative interference suppression algorithm .3is designed and implemented in downlink base station cooperative system. A distributed generalized zero forcing coding algorithm based on generalized approximate message passing is designed and implemented. Firstly, the partial precoding algorithm in multiuser systems is studied, in which generalized zero forcing precoding achieves a good compromise in complexity and performance. It can restrain ICI effectively when it is used in centralized cooperative system. However, the implementation of centralized cooperative precoding is limited by complexity and limited backhaul capacity. In this paper, a distributed generalized zero forcing precoding algorithm based on generalized approximate messaging is proposed.
【学位授予单位】：郑州大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN929.5

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