短循环前缀OFDM信号参数估计方法研究  

Study on Parameter Estimation for the Short Length Cyclic Prefix OFDM Signal

作　　者：张海川[1,2] 雷迎科[1,2] 

机构地区：[1]电子工程学院,安徽合肥230037 [2]通信信息控制和安全技术重点实验室,浙江嘉兴314033

出　　处：《信号处理》2016年第12期1489-1496,共8页Journal of Signal Processing

基　　金：国家自然科学基金资助项目(61272333);国防科技重点实验室基金(9140C130502140C13068);解放军总装备部预研项目基金(9140A33030114JB39470);安徽省自然科学基金资助项目(1308085QF99)

摘　　要：为了克服传统的OFDM信号参数估计方法在短循环前缀条件需要大量OFDM符号、估计性能较低、抗多径衰落能力差等缺点,本文提出了一种新的短循环前缀OFDM信号参数估计方法。该算法利用OFDM信号模型推导出接收端的傅里叶逆变换模型函数,然后在此基础上根据OFDM信号的先验概率密度构造一种多参数融合的极大似然函数,并从理论上说明了可以通过检测似然函数的最小值实现OFDM信号循环前缀长度和有效符号长度的联合估计。同时,本文还利用动态粒子群优化算法(DPSO)降低了搜索复杂度,缩短了估计时间。仿真实验展示本文算法在不同环境下对OFDM信号参数估计的鲁棒性,表明本文算法的识别性能优于传统方法。In order to overcome the shorticomings of traditional parameters estimation methods for the short length OFDM signal that required lots of OFDM symbols, and had the poor performance and the poor anti multipath fading capability. This paper presented a novel method to estimate the parameters for short cyclic prefix length OFDM signal. The method used the OFDM signal model to compute the model function of inverse fourier transform, and according the prior probability density of OFDM signal, we construct the maximum likelihood function of multi parameter fusion on the basis of model function and theoretically demonstrated that the joint estimation for cyclic-prefix length and useful symbol length can be achieved by detecting the lowest value of maximum likelihood function. In addition, we used dynamic particle swarm optimization algorithm（DPSO） to reduce computational complexity and shorten the estimated time. The experimental results illustrate the robustness of the proposed algorithm to estimate the parameters for short CP OFDM signal under various circumstance, and show that the proposed algorithm has better performance than conventional algorithm.

关 键 词：正交频分复用(OFDM) 极大似然函数 循环前缀 动态粒子群优化算法 

分 类 号：TN911.7[电子电信—通信与信息系统]