MIMO干扰信道中联合功率分配和干扰对齐算法研究

发布时间：2018-04-23 02:28

本文选题：MIMO + 干扰对齐　；参考：《南京邮电大学》2017年硕士论文

【摘要】：随着移动通信的普及和广泛应用,用户在生活中更多的通过移动终端来接入网络,再加上频谱是极为有限的资源,这就给系统容量带来巨大挑战。MIMO系统在发送功率和系统带宽不增加的情况下可以大幅度的提高系统的频谱利用率,但随之而来的就是频谱共享带来的多用户间的干扰问题。干扰管理技术中的一种叫做干扰对齐的技术,比传统干扰管理技术性能更好,成为移动通信领域研究的热点。本文首先对MIMO系统和干扰对齐技术中的基本概念进行介绍,给出了时域、频域、空域下干扰对齐的实现方式。接着介绍了最大化信干噪比、最小化加权干扰泄露、最小均方误差及交替最小化四种分布式干扰对齐算法。之后对K用户MIMO干扰网络进行深入研究,经典干扰对齐方案中忽略了有用信号所经历的信道环境,系统容量没有达到最优。针对这一问题,给出一种基于SVD分解的预编码矩阵优化方法,该方法通过对信道矩阵作SVD分解,根据信道增益特性选出最优的特征子信道,然后在矩阵弦距离准则的基础上,选取与最优特征子信道最为匹配的预编码矩阵,从而使得接收端信号强度和系统容量得到显著改善。最后,针对传统干扰对齐技术没有考虑功率分配的缺陷而造成系统资源没有得到充分利用的情况,给出一种联合功率分配和干扰对齐算法,该算法在交替最小化算法的基础上引入改进的注水功率分配算法,给发射端的数据流分配功率,此算法既可以利用干扰对齐技术来消除干扰,又可以通过改进的注水功率分配算法来提高系统的总吞吐量,通过仿真比较所提算法与等功率分配时的交替最小化干扰对齐算法的系统性能,显示出所提算法有效地提高了系统吞吐量且降低了总干扰功率。
[Abstract]:With the popularity and wide application of mobile communication, users are more and more connected to the network through mobile terminals in their daily lives. In addition, the spectrum is a very limited resource. This brings great challenges to the system capacity. MIMO system can greatly improve the spectrum efficiency without increasing transmission power and system bandwidth, but the problem of multi-user interference caused by spectrum sharing follows. One of the interference management techniques called interference alignment is better than the traditional interference management technology and has become a hotspot in the field of mobile communication. In this paper, the basic concepts of MIMO system and interference alignment technology are introduced, and the implementation of interference alignment in time domain, frequency domain and spatial domain is given. Then four distributed interference alignment algorithms including maximization of signal-to-noise ratio, minimization of weighted interference leakage, minimum mean square error and alternating minimization are introduced. Then the K-user MIMO jamming network is deeply studied. The channel environment experienced by the useful signal is neglected in the classical jamming alignment scheme and the system capacity is not optimal. In order to solve this problem, a precoding matrix optimization method based on SVD decomposition is presented. By SVD decomposition of channel matrix, the optimal characteristic subchannel is selected according to channel gain characteristics, and then based on the matrix chord distance criterion, the optimal characteristic subchannel is selected according to the channel gain characteristics. The precoding matrix that matches the optimal feature subchannel is selected to improve the signal strength and system capacity of the receiver. Finally, a joint power allocation and interference alignment algorithm is proposed to solve the problem that the traditional interference alignment technology does not take power allocation into account and the system resources are not fully utilized. Based on the alternating minimization algorithm, an improved water injection power allocation algorithm is introduced to allocate power to the data stream of the transmitter. This algorithm can eliminate the interference by using the interference alignment technique. The total throughput of the system can be improved by the improved water injection power allocation algorithm, and the system performance of the proposed algorithm and the alternative minimization interference alignment algorithm with equal power allocation can be compared by simulation. It shows that the proposed algorithm can effectively improve the system throughput and reduce the total interference power.
【学位授予单位】：南京邮电大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN919.3

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