计算机应用 ›› 2014, Vol. 34 ›› Issue (10): 2787-2790.DOI: 10.11772/j.issn.1001-9081.2014.10.2787

• 网络与通信 • 上一篇    下一篇

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

杨朝阳1,杨霄鹏1,李腾1,姚昆1,2,倪娟3   

  1. 1. 空军工程大学 信息与导航学院,西安 710077
    2.
    3. 94303部队,山东 潍坊 261100
  • 收稿日期:2014-04-28 修回日期:2014-06-12 出版日期:2014-10-01 发布日期:2014-10-30
  • 通讯作者: 杨朝阳
  • 作者简介:杨朝阳(1989-),男,陕西宝鸡人,硕士研究生,主要研究方向:OFDM频偏估计;
    杨霄鹏(1973-),男,甘肃天水人,副教授,博士,主要研究方向:宽带无线通信、信号处理;
    李腾(1990-),男,陕西西安人,硕士研究生,主要研究方向:VOIP、时延预测算法;
    姚昆(1975-),女,陕西西安人,副教授,硕士,主要研究方向:频谱管理、信号处理;
    倪娟(1988-),女,湖北黄冈人,硕士,主要研究方向:Rake接收技术。
  • 基金资助:

    国家自然科学基金资助项目;航空科学基金资助项目

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

YANG Zhaoyang1,YANG Xiaopeng1,LI Teng1,YAO Kun1,NI 3   

  • Received:2014-04-28 Revised:2014-06-12 Online:2014-10-01 Published:2014-10-30
  • Contact: YANG Zhaoyang

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。

Abstract:

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).

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