机会干扰对齐与盲干扰对齐技术研究

发布时间：2018-07-29 06:23

【摘要】：干扰对齐(Interference Alignment,IA)是目前的研究热点,该技术能有效提高干扰网络的容量,改善传统方式中有线和无线网络吞吐量受限的问题。其核心思想是将干扰信号压缩到尽可能小的干扰空间中,以预留更多的空间无干扰的传输有用信号。研究表明,在理想情况下,如全局信道信息、无限的分辨率及带宽、高信号强度和延迟等,干扰对齐能够提供最优的信道自由度。然而,在实际通信过程中,干扰对齐技术的应用仍面临很多挑战:迭代干扰对齐算法的复杂度高;干扰的对齐需要比较高的信号维度;中继辅助干扰对齐算法对时变信道适应能力差。本文针对实际系统中存在的若干问题展开研究,提出相应的干扰对齐算法。1.针对传统迭代干扰对齐算法复杂度高的问题,研究了机会干扰对齐及其改进算法。机会干扰对齐利用用户分集,选择信道较好的用户,降低了系统中的干扰泄漏程度,从而达到干扰对齐的目的。但是,在实际的通信系统中,可供选择的用户数目较少,系统中干扰泄漏的可能性增大,这制约了机会干扰对齐算法的性能。针对此问题,提出了机会干扰对齐改进算法。具体的,以各用户干扰泄漏矩阵的最小特征值为度量,选取干扰泄漏最小的用户进行通信。同时,结合信道状态信息及用户波束成形的信息,基站可通过奇异值分解(Singular Value Decomposition,SVD)选取滤波器,使干扰方向更有效的压缩在干扰空间内。另外,针对实际系统中获得的信道状态信息存在误差的问题,提出了能有效提高信干噪比的干扰对齐改进算法。该算法通过降低系统中可确定的干扰功率,进而减少系统总的干扰信号功率。2.针对实际系统中信号空间维度不够高且完美信道状态信息获取难的问题,研究了K个用户SISO干扰信道的盲干扰对齐算法。算法利用非对称复信号(Asymmetric Complex signaling,AC signaling)的设计,增加了信号空间的维度,有效地解决了单天线约束问题,从而实现了盲干扰对齐。此外,本文证明了K个用户干扰信道的系统自由度达到K/2,这同时也是发射端信道状态信息已知时系统自由度的上限。并对其系统性能通过仿真验证。3.针对中继辅助干扰对齐算法对时变信道适应能力差且算法计算复杂度高的问题,提出了改进的干扰对齐算法。首先,在中继SISO系统中,利用AC signaling的设计,增加了信号空间的维度,有效解决中继辅助的有限信道符号扩展的问题。分析了中继端通过信道信息设计接收端的滤波器,实现干扰对齐,并仿真验证了与用户间无干扰理想情况的性能相当。其次,针对节点天线数对系统吞吐量的影响与约束,研究了中继MIMO系统的干扰对齐算法,中继端通过合理设计中继处理矩阵,使干扰达到最小或完全消除。与中继迭代干扰对齐算法相比,降低了系统复杂度。最后,为改善半双工中继造成的容量损失,研究了两个中继交替转发的干扰对齐算法。该算法有效提高了时隙的利用率,从而改善系统的性能,并通过仿真验证。
[Abstract]:Interference Alignment (IA) is the focus of current research. This technology can effectively improve the capacity of interference network and improve the throughput Limited of wired and wireless networks in traditional methods. The core idea is to compress the interference signal into the small interference space to save more space without interference. The research shows that, in the ideal case, such as global channel information, infinite resolution and bandwidth, high signal intensity and delay, interference alignment can provide the optimal channel freedom. However, in the actual communication process, the application of interference alignment technology still faces many challenges: the complexity of the iterative interference alignment algorithm is high; the interference is the same. It needs a higher signal dimension, and the adaptive interference alignment algorithm is poor in adaptability to the time-varying channel. In this paper, a number of problems existing in the actual system are studied, and the corresponding interference alignment algorithm.1. is proposed for the problem of high complexity of the traditional iterative interference alignment algorithm, and the opportunity interference alignment and its improved algorithm are studied. However, in the actual communication system, the number of users selected is less and the possibility of interference leaks in the system increases, which restricts the performance of the opportunity interference alignment algorithm. In this problem, an improved algorithm for opportunity interference alignment is proposed. Specifically, using the minimum eigenvalue of the interference leakage matrix of each user, the users of the least interference leakage are selected to communicate. At the same time, the base station can select the filter through the Singular Value Decomposition (SVD), combining the channel state information and the information of the user beamforming. In addition, an improved jamming alignment algorithm which can effectively improve the signal to noise ratio is proposed. This algorithm reduces the total interference power.2 of the system by reducing the determined interference power in the system. In view of the problem that the dimension of the signal space is not high and the perfect channel state information is difficult to obtain in the actual system, the blind interference alignment algorithm of K SISO interference channel is studied. The algorithm uses asymmetric complex signal (Asymmetric Complex signaling, AC signaling) to increase the dimension of the signal space, and effectively solves the single antenna approximately. In addition, this paper proves that the system freedom degree of the K user interference channel is K/2, which is also the upper limit of the system freedom degree when the channel state information is known at the transmitter. And the performance of the system is verified by the simulation of the performance of the.3.. And the algorithm has high computational complexity, and an improved interference alignment algorithm is proposed. First, in the relay SISO system, using the design of AC signaling, the dimension of the signal space is added, and the problem of the relay assisted finite channel symbol expansion is effectively solved. The filter of the relay terminal through channel information design receiver is analyzed. The interference alignment and simulation prove that the performance of the undisturbed ideal situation is equal to the user. Secondly, the interference alignment algorithm of the relay MIMO system is studied in the light of the influence and constraints of the number of nodes on the system throughput. The relay ends the interference to minimize or completely eliminate the interference by designing the relay processing matrix properly. The interference alignment with the relay is aligned with the relay. Compared with the algorithm, the complexity of the system is reduced. Finally, in order to improve the capacity loss caused by the half duplex relay, the interference alignment algorithm of two relay alternate forwarding is studied. The algorithm improves the utilization of the time slot effectively, and improves the performance of the system, and the simulation is verified by simulation.
【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】：TN972

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