摘要
针对现有的正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)频偏估计算法普遍存在估计范围小,估计精度不高的问题,提出了一种新的训练序列频率同步算法.首先采用缩短训练序列和周期性发送序列的方式,增大了频偏估计的范围,但频偏范围的增大会导致性能的损失;然后又提出一种通过对短周期重复样式的估计值取平均的方法,在保持估计范围不变的情况下,进一步的提高了频偏估计的性能.最后仿真结果表明,改进的算法频偏估计范围大,并且估计精度较高,均方误差(Mean Square Error,MSE)可以达到10^-6.
Aiming at the problems of the existing Orthogonal Frequency Division Multiplexing(OFDM)frequency offset estimation algorithms,which have a small estimation range and low estimation accuracy,a new training sequence frequency synchronization algorithm is proposed.Firstly,the training sequence and periodic transmission sequence are shortened to increase the range of frequency offset estimation.However,the increase of the frequency offset range will result in a loss of performance.Then,a method is proposed by averaging the estimated values of the short-period repetitive patterns.The performance of the frequency offset estimation is further improved while the estimation range is maintained.Finally,simulation results show that the improved algorithm has a large frequency offset estimation range and high estimation accuracy,and the Mean Square Error(MSE)can reach 10^-6.
作者
商林松
龙华
李一民
邵玉斌
杜庆治
SHANG Lin-song;LONG Hua;LI Yi-min;SHAO Yu-bin;DU Qing-zhi(Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500,China;Computer Technology Application Key Lab of Yunnan Province,Kunming 650500,China)
出处
《云南大学学报（自然科学版）》
CAS
CSCD
北大核心
2020年第4期630-637,共8页
Journal of Yunnan University(Natural Sciences Edition)
基金
国家自然科学基金(61761025).
关键词
正交频分复用
频率同步
训练序列
均方误差
Orthogonal Frequency Division Multiplexing(OFDM)
frequency synchronization
training sequence
Mean Square Error(MSE)
