Acta Scientiarum Naturalium Universitatis Pekinensis

Previous Articles     Next Articles

An Iterative Carrier Frequency Estimation Algorithm

LUO Wu, LIU An, LIANG Qinglin   

  1. School of Electronics Engineering and Computer Science, Peking University, Beijng 100871;
  • Received:2007-07-12 Online:2008-07-20 Published:2008-07-20

一种迭代频偏估计算法

罗武,刘安,梁庆林   

  1. 北京大学信息科学技术学院,北京100871;

Abstract: An iterative data-aided algorithm based on maximum likelihood (ML) for carrier frequency estimation under low signal-to-noise ratio (SNR) environment is proposed. Simulation results show that it can achieve about 3dB lower SNR threshold when compared with M&M algorithm. Its estimation range is large, about 40% of the symbol rate and its accuracy is very close to FFT-based maximum likelihood frequency estimation algorithm and the Cramer-Rao lower bound (CRLB). Moreover, the simplified estimator based on proposed algorithm has both lower threshold and less computational complexity when compared with iterative linear prediction (ILP) algorithm.

Key words: carrier synchronization, frequency estimation, data aided, iterative estimation, Cramer-Rao lower bound(CRLB)

摘要: 提出一种适于低信噪比条件下工作的数据辅助型(data-aided)频偏估计算法。计算接收信号自相关函数的辐角,基于最大似然策略合成频偏估计,并通过迭代消除估计模糊。仿真结果表明:迭代算法具有较大的频偏估计范围(估计范围达±40%符号速率),与M&M算法相比,迭代算法信噪比门限有接近3dB性能改善,其估计性能更接近FFT最大似然算法和克拉美-劳下界(CRLB),并且计算量有所降低;基于迭代算法的简化版本与迭代线性预测(ILP)算法相比信噪比门限更低,并且降低了计算复杂度。

关键词: 载波同步, 频率估计, 数据辅助, 迭代估计, 克拉美-劳下界(CRLB)

CLC Number: