基于萤火虫算法优化电调天线下倾角研究

发布时间：2018-08-18 21:37

【摘要】：随着移动通信技术的飞速发展,日益增长的网络容量需求和网络资源的高效利用率,成为当前无线产业商亟待解决的问题。对于2G,3G,4G或5G网络而言,合理的基站天线选择与下倾角调节是提升蜂窝网络性能的必要方式。因此,论文提出基于萤火虫算法优化调节电调天线下倾角以提升蜂窝网络系统的性能。研究主要包括以下内容:1.电调天线下倾角数学模型建立。首先建立蜂窝网络3×1扇形分区模型和基站天线下倾角模型,利用电调天线在垂直维度增加的自由度的特性,使用泰勒级数展开式对垂直天线增益进行近似表达,然后根据近似所得的天线增益与路损模型推导出信号与干扰加噪声比(Signal to Interference plus Noise Ratio,SINR)的公式,得出天线下倾角与系统优化目标函数的关系,实现最优化问题的定义。2.标准萤火虫算法的原理阐述。根据自然界中萤火虫群体的发光特性,从算法的仿生原理、参数定义、参数分析以及算法优化流程四个方面对萤火虫算法迭代搜索最优值原理进行分析。并通过相关仿真分析,说明标准萤火虫算法的种群规模、光强吸收系数与步长因子等参数的不同取值对算法的优化速度、收敛精度以及全局优化搜索等性能的影响。3.改进萤火虫算法的研究分析。针对标准萤火虫算法在优化搜索后期容易出现的收敛精度低和局部优化搜索的问题,对算法进行功能化改进,并结合关键参数对算法的影响,给出基于惯性权重、收敛因子以及混沌映射的改进萤火虫算法。通过仿真多元经典峰值测试函数来比较标准算法和改进算法在求解待优化问题时的优化能力,说明改进算法的高效性。4.电调天线下倾角优化问题的研究。使用萤火虫算法对蜂窝网络中基站扇区下倾角进行优化调节时,考虑到在全局范围内优化多个扇区下倾角时所需的信息量很大,而且算法实现也具有较高的复杂度,提出一种分布式优化调节方式来联合优化所有的扇区下倾角。另外,考虑小区独立优化的特殊情况,还给出基于单小区下倾角优化调节方案,作为电调天线下倾角优化研究的补充说明。
[Abstract]:With the rapid development of mobile communication technology, the increasing demand for network capacity and the efficient utilization of network resources have become the urgent problems to be solved by wireless industry. For 2GN 3GN 4G or 5G networks, reasonable base station antenna selection and downdip adjustment are necessary to improve cellular network performance. Therefore, a firefly algorithm is proposed to optimize the tuning of the dip angle of the electric antenna to improve the performance of the cellular network system. The research mainly includes the following contents: 1: 1. The mathematical model of the downdip angle of the electrically tuned antenna is established. Firstly, the 3 脳 1 sector partition model of cellular network and the downdip angle model of base station antenna are established, and the gain of vertical antenna is approximately expressed by Taylor series expansion by using the characteristic of increasing the degree of freedom in vertical dimension of electrically tuned antenna. Then, according to the approximate antenna gain and path loss model, the formula of the ratio of signal to interference plus noise (Signal to Interference plus Noise) is derived, and the relationship between the antenna dip angle and the optimization objective function of the system is obtained, and the definition of optimization problem is obtained. The principle of standard firefly algorithm is expounded. According to the luminescence characteristics of the firefly population in nature, the principle of iterative searching optimal value of the algorithm is analyzed from four aspects: bionic principle, parameter definition, parameter analysis and algorithm optimization process. The effects of population size, light intensity absorption coefficient and step size factor on the optimization speed, convergence accuracy and global optimization search of the standard firefly algorithm are discussed. Research and Analysis of improved Firefly algorithm. Aiming at the problems of low convergence accuracy and local optimal search in the late stage of optimization search of standard firefly algorithm, this paper improves the algorithm function, and gives the inertia weight based on the influence of key parameters on the algorithm. Convergence factor and improved firefly algorithm for chaotic mapping. The optimization ability of the standard algorithm and the improved algorithm in solving the problem to be optimized is compared by simulating the multivariate classical peak test function, and the efficiency of the improved algorithm. 4. Research on the optimization of dip angle of an electrically tuned antenna. When the firefly algorithm is used to optimize the downdip angle of base station in cellular network, the amount of information needed to optimize the dip angle of multiple sectors in the global range is considered, and the implementation of the algorithm has a high complexity. A distributed optimization adjustment method is proposed to jointly optimize the dip angles of all sectors. In addition, considering the special case of cell independent optimization, the scheme of dip angle optimization based on single cell is presented, which is used as a supplementary explanation for the research of downdip angle optimization of electrically tuned antenna.
【学位授予单位】：安徽大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN828.6

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