摘要
快速准确的载波频偏估计在突发信号的相干解调中发挥着至关重要的作用。目前的载波频偏估计算法很难同时兼顾估计精度、信噪比(signal-to-noise ratio,SNR)门限以及估计范围等指标。针对这一问题,提出了一种数据辅助的基于接收信号自相关序列离散傅里叶变换(discrete Fourier transform,DFT)的载波频偏估计算法。该算法通过对接收信号的自相关进行加窗处理,借助离散傅里叶变换来实现频率估计。仿真结果表明,与经典的M&M算法相比,该算法具有更低的信噪比工作门限,在低信噪比情况下具有更低的差错概率和更宽的估计范围,非常适合低信噪比突发信号的载波频偏估计。
Fast and accurate carrier frequency offset estimation is very important in the coherent demodula- tion for the burst signal. There are some dilemmas in the traditional carrier frequency estimation algorithm, such as estimation accuracy, signal-to-noise ratio （SNR） threshold and estimation range, etc. Aim to these problems, a data aided carrier frequency offset estimation algorithm for burst and low SNR signal is put forward based on the discrete Fourier transform （DFT） of the auto correlation of the received signal. The carrier fre- quency offset can be estimated by windowing to the received signal autocorrelation and DFT. The simulation re- sults show that, compared with the M＆M algorithm, the lower SNR threshold, lower error probability and higher estimation range in the low SNR conditions are achieved for the algorithm. It is very suitable for carrier frequency offset estimation for the burst and low SNR signal.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2015年第12期2848-2852,共5页
Systems Engineering and Electronics
基金
中国博士后科学基金(2013M542485)资助课题
关键词
载波频偏估计
低信噪比
突发信号
M&M算法
carrier frequency offset estimation
low signal to noise ratio（SNR）
burst signal
M＆M algorithm
