【作者】 张涛；

【导师】 谢红；

【作者基本信息】 哈尔滨工程大学 ， 通信与信息系统， 2009， 硕士

【摘要】 近年来,随着通信产业的高速发展,智能天线技术已成功应用于移动通信系统,并通过对无线数字信号的高速时空处理,不但增加了信道容量,提高了频谱效率,也扩展了覆盖范围。未来我国将进入3G,4G的高速建设发展期,智能天线技术将会迎来广阔的发展空间。本文首先介绍了智能天线的基本结构,工作原理和信号模型,同时分析了遗传算法的基本步骤和特点。另外在研究了智能天线波达角估计算法中的MUSIC算法和波束空间MUSIC算法的原理和信号模型的基础上,提出了高分辨处理的一种波束空间中的改进MUSIC算法,仿真实验结果表明,和传统的波束空间MUSIC算法相比,改进算法的分辨信噪比门限值更低。另外,波束形成技术源于智能天线,增强期望、抑制用户干扰是其独特的技术优势,也是空分多址(SDMA)得以实现的基础。同时本文研究了智能天线中的自适应波束形成的基本算法,包括最陡下降法,最小均方算法和最小二乘算法。目前,遗传算法在解决该类方向图优化问题上已经成为了研究热点。但是遗传算法也存在收敛速度慢、易早熟、局部搜索能力差等缺点。对于多目标多参数的方向图非线性优化问题,遗传算法在搜索速度与求解精度上往往不能两者兼顾。因此,本文提出了一种基于遗传算法和禁忌搜索算法的混合遗传算法的波束形成技术研究,该算法既具有遗传算法的全局寻优能力,又具有禁忌搜索算法的局部寻优能力,可大大提高寻优的速度和精度。本文分别进行了混合遗传算法和传统遗传算法在相同参数设置下的仿真对比分析,以及混合遗传算法在不同参数设置下的仿真对比分析,仿真实验结果表明,基于混合遗传算法的波束形成方法能在保证搜索质量的前提下极大的提高了寻优效率,提高了运算速度。更多还原

【Abstract】 In recent years, with the development of communications, smart antenna technology has been used in the field of mobile communications successfully. By the means of space-time processing to the wireless digital signals, the efficiency of the frequency’s usage is improved extremely. In the future, our country will enter the period of 3G and 4G. So we can see that the smart antenna technology would be used widely.First, the paper introduces the basic structure, work principle and signal model of smart antenna. In the meantime it analyzes the basic step and characteristic of Genetic Algorithms (GA).Then it discusses MUSIC algorithm and MUSIC algorithm based on beamspace including principle and signal model of Direction of Arrivals (DOA) on smart antenna. Based on this, the paper proposes a modified MUSIC algorithm based on beamspace for high resolution array processing, simulation results show the threshold signal-to-noise ratio of the modified algorithm is lower than the one of basic algorithm.Besides, Beamforming stems from smart antenna, with increasing desire signal and suppressing interference as its technical superiority, which is also the foundation for the realization of SDMA. In the meantime the paper discusses the study of adaptive algorithms on smart antenna including steepest descent algorithm, least mean square algorithm and recursive least squares. GA has become the research hot point in the optimization of antenna array pattern synthesis. But GA has some disadvantages such as slow convergence speed, easy to be premature, bad local search capability. Based on the problem of non-linear multi-objective and multi-parameter optimization, it can’t meet the requirements of search speed and solution precision simultaneously. Therefore the paper proposes a beamforming technology research based on GA and Tabu Search (TS) algorithms. The hybrid genetic algorithms has both the capability of the optimization of GA in the global area and that of TS algorithms in the local area, and it greatly improves the search speed and precision. The paper simulates and analyzes the differences between the hybrid genetic algorithms and the basic genetic algorithms with the same parameters. And also simulates and analyzes the performance of the hybrid genetic algorithms with the different parameters. Simulation results show that the beamforming techniques based on the hybrid GA enormously enhance the efficiency of optimization and raise the operating rate, guarantee the quality of searching as a prerequisite.更多还原