关键词: 帧定时同步, 模式化压缩感知, 同步度量, 基于模式化压缩的采样匹配追踪（CoSaMP）

Abstract: As a prerequisite of data detection, the frame timing synchronization has been become the hot topic and the key issue of the communication. However, the existing methods without adopting Compressive Sensing（CS） method have to meet the Nyquist rate, resulting in excessive power consumption and design difficulty for analog-to-digital converter. Furthermore, the correct synchronization probability needs to be improved when the compressive sensing method is adopted. To improve the correct synchronization probability, this paper introduces the model-based CS theory into frame timing synchronization, and a new improved method named model-based Compressive Sampling Matching Pursuit（CoSaMP） algorithm is proposed. In the proposed method, the synchronization metrics from the compressive sampling are reconstructed by utilizing model-based CoSaMP, and the start of frame is then estimated with the reconstructed metrics. Compared to the existing CS-based, analysis and simulation results show that the correct synchronization probability is improved.

Key words: frame timing synchronization, model-based compressed sensing, synchronization metrics, Compressive Sampling Matching Pursuit（CoSaMP）