新的基于粒子群优化的正交频分复用系统盲频偏估计算法  

Novel blind frequency offset estimation algorithm in orthogonal frequency division multiplexing system based on particle swarm optimization

作　　者：杨朝阳[1] 杨霄鹏[1] 李腾[1] 姚昆[1] 倪娟[2] 

机构地区：[1]空军工程大学信息与导航学院 [2]94303部队

出　　处：《计算机应用》2014年第10期2787-2790,2795,共5页journal of Computer Applications

基　　金：国家自然科学基金资助项目(61202490);航空科学基金资助项目(2013ZC15008)

摘　　要：针对正交频分复用(OFDM)系统频偏估计问题,提出了一种基于粒子群优化(PSO)的盲频偏估计算法。首先,根据频偏估值重建的接收信号和实际接收到的信号误差最小原则构造了盲频偏估计的数学模型,并推导出了代价函数;然后,利用粒子群优化算法强大的随机并行全局搜索能力,通过最小化代价函数估计频偏。仿真比较了常系数、微分递减两种惯性权重策略PSO算法的频偏估计性能,并与最小输出方差、黄金分割盲频偏估计算法进行了比较分析。仿真结果表明,所提算法精度高,同一信噪比下较同类算法大约有一个数量级的提升,且不受调制类型和频偏估计范围(-0.5,0.5)的限制。To estimate the frequency offset in Orthogonal Frequency Division Multiplexing （OFDM） system, a novel blind frequency offset estimation algorithm based on Particle Swarm Optimization （PSO） method was proposed. Firstly the mathematical model and cost function were designed according to the principle of minimum reconstruction error of the reconstructed signal and the signal actually received. The powerful random, parallel, global search property of PSO was utilized to minimize the cost function to get the frequency offset estimation. Two inertia weight strategies for PSO algorithm of constant coefficient and differential descending were simulated, and comparison was made with the minimum output variance and gold section methods. The simulation results show that the proposed algorithm performs highly accuracy, about one order of magnitude higher than other similar algorithms in same Signal-to-Noise Ratio （SNR） and it is not restricted by modulation type and frequency estimation range （-0.5,0.5）.

关 键 词：正交频分复用 载波频偏 盲频偏估计 码分多址 粒子群优化 

分 类 号：TN911.7[电子电信—通信与信息系统]