Acta Scientiarum Naturalium Universitatis Pekinensis

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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



  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)

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