As a critical technology of 5G air interface waveform, filtered orthogonal frequency division multiplexing (F-OFDM) not only inherits the technical advantages of OFDM, but also has outstanding advantages in system flexibility and spectrum efficiency. However, as a multi-carrier technology, it is still extremely sensitive to sample timing offset (STO) and carrier frequency offset (CFO). In this letter, an improved Park frequency domain training sequence (FS-Park) is proposed to complete STO and CFO estimation of F-OFDM system. Firstly, a real-value pseudorandom number (PN) sequence is sent to each subcarrier as training sequence in frequency domain, the corresponding time domain training symbol has a conjugate symmetry structure. Secondly, the training symbol is utilized for timing synchronization, then the fractional frequency offset is estimated based on the cyclic prefix in time domain. Finally, the integer frequency offset is estimated in frequency domain based on the auto-correlation of PN sequence. The simulation results illustrate that the FS-Park algorithm not only has a single pulse timing metric curve and great STO estimation accuracy, but also has better performance of CFO estimation than classical Park algorithm and Liang Xiao’s method.

作为5G空口波形的一项关键技术，滤波正交频分复用（F-OFDM）不仅继承了OFDM的技术优势，而且在系统灵活性和频谱效率方面拥有突出的优势。但是，作为一种多载波技术，它对采样时序偏移（STO）和载波频率偏移（CFO）仍然非常敏感。在这封信中，提出了一种改进的Park频域训练序列（FS-Park），以完成F-OFDM系统的STO和CFO估计。首先，将实值伪随机数（PN）序列作为频域中的训练序列发送给每个子载波，对应的时域训练符号具有共轭对称结构。其次，训练符号用于时序同步，然后根据时域中的循环前缀来估算分数频率偏移。最后，基于PN序列的自相关，在频域中估计整数频率偏移。仿真结果表明，FS-Park算法不仅具有单脉冲时序度量曲线和较高的STO估计精度，而且具有比传统Park算法和Liang Xiao方法更好的CFO估计性能。