智能天线自适应波束形成算法的研究

发布时间：2018-04-01 06:17

本文选题：智能天线　切入点：自适应波束形成　出处：《东北大学》2014年硕士论文

【摘要】：智能天线技术作为现代通信领域的研究热点,已成功的应用到无线通信系统中。智能天线引进了空分多址技术,能够与其他多址技术相结合,使通信资源由时间域、频率域、码域扩展到空间域,有效地增大了系统的容量,最大限度的利用有限的频谱资源,并将会在未来移动通信系统中发挥重要作用。自适应波束形成技术是智能天线的核心技术,它能够自适应地控制天线阵方向图在用户信号方向产生高增益窄波束,在干扰信号方向产生较深的零陷,是实现用户信号最佳接收的有效方法。本文围绕自适应波束形成算法展开研究,在总结前人工作的基础上,提出了一些改进算法,主要工作如下：首先,本文对目前国内外智能天线技术及自适应波束形成算法的研究现状进行了综述,并介绍了自适应波束形成技术中的最佳加权准则。其次,本文研究了经典的最小均方(Least Mean Square, LMS)算法,并对SVSLMS算法和MSVSLMS算法进行了重点仿真研究和数学分析,针对这两种算法的缺陷提出了一种改进的算法,该算法是基于双曲余弦函数的变步长LMS算法,通过定义新的步长函数,改进了上述算法的缺点,仿真结果证明了所提出算法的有效性。再次,本文详细分析了周期自适应波束形成(Cyclic Adaptive Beamforming, CAB)类算法,其中约束周期自适应波束形成算法(Constrained CAB, CCAB)在低信号干扰噪声比情况下性能很差,为解决上述问题,本文提出一种改进的基于特征空间的CAB算法(ECAB),该算法利用信号子空间约束来提高算法的鲁棒性。大量的计算机仿真实验验证了本文改进算法的有效性。最后,对本文的研究工作进行了总结,并对未来的研究工作进行了展望。
[Abstract]:As a research hotspot in modern communication field, smart antenna technology has been successfully applied to wireless communication systems.Smart antenna introduces space division multiple access (SDMA) technology, which can combine with other multiple access technologies to extend communication resources from time domain, frequency domain and code domain to space domain, which effectively increases the capacity of the system and maximizes the use of limited spectrum resources.And will play an important role in the future mobile communication system.Adaptive beamforming is the core technology of smart antenna. It can adaptively control the antenna array pattern to produce high gain narrow beam in the direction of user signal and deep zero trapping in the direction of interference signal.It is an effective method to realize the optimal reception of user signal.In this paper, the adaptive beamforming algorithm is studied. On the basis of summarizing the previous work, some improved algorithms are proposed. The main work is as follows: first,In this paper, the research status of smart antenna technology and adaptive beamforming algorithm at home and abroad is reviewed, and the optimal weighting criterion in adaptive beamforming technology is introduced.Secondly, this paper studies the classical least mean square Mean squared (LMS) algorithm, and focuses on the simulation and mathematical analysis of SVSLMS algorithm and MSVSLMS algorithm, and proposes an improved algorithm for the defects of these two algorithms.This algorithm is a variable step size LMS algorithm based on hyperbolic cosine function. By defining a new step size function, the shortcomings of the above algorithm are improved. The simulation results show that the proposed algorithm is effective.Thirdly, the periodic adaptive beamforming algorithm, cyclic Adaptive beam forming algorithm, is analyzed in detail. The constrained periodic adaptive beamforming algorithm (CCABs) has poor performance in the case of low signal interference noise ratio.An improved feature space-based CAB algorithm is proposed in this paper. The algorithm uses signal subspace constraints to improve the robustness of the algorithm.A large number of computer simulation experiments verify the effectiveness of the improved algorithm.Finally, the research work of this paper is summarized, and the future research work is prospected.
【学位授予单位】：东北大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN821.91

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