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一种采用可变同步帧的OFDM符号定时同步算法
张羽丰,陈青岳,李炯卉,王竹刚,熊蔚明
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(1.中国科学院 国家空间科学中心 复杂航天系统电子信息技术重点实验室,北京101400;2.中国科学院大学,北京100049;3.北京空间飞行器总体设计部,北京100094)
摘要:
符号定时同步是正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)系统中最为关键的同步之一。针对现有的基于数据辅助类的同步算法中帧头存在持续时间长、抗噪声性能差和对载波频偏敏感等问题,提出了一种可变长度的同步帧结构,采用滑动差分相关算法完成符号定时同步。仿真结果表明,提出的同步帧结构持续时间短于一个OFDM符号周期,并且训练序列长度可以通过估算信噪比大小而灵活控制。同时,所提算法在归一化载波频偏为12(远远超过晶振的误差范围 ±10-5)的情况下正常工作;在高斯白噪声和多径衰落信道中都有较好的性能,且其流水线结构易于硬件实现。
关键词:  正交频分复用  符号定时同步  可变同步帧  训练序列  差分相关
DOI:
基金项目:国家自然科学基金资助项目(11672293)
An OFDM Timing Synchronization Algorithm Using Variable Synchronization Frames
ZHANG Yufeng,CHEN Qingyue,LI Jionghui,WANG Zhugang,XIONG Weiming
(1.Key Laboratory of Electronics and Information Technology for Space Systems,National Space Sciences Center, Chinese Academy of Sciences,Beijing 101400,China;2.University of Chinese Academy of Sciences,Beijing 100049,China;3.Beijing Institute of Spacecraft System Engineering,Beijing 100094,China)
Abstract:
Timing synchronization is one of the most critical synchronizations in orthogonal frequency division multiplexing(OFDM) systems.In most data-aided timing synchronization algorithms,the training sequence features a long duration.Besides,these algorithms generally have a poor synchronization performance in noisy environment,and are sensitive to carrier frequency offsets(CFO).To deal with those problems,a new sliding differential correlation algorithm using a variable-length training sequence is proposed.Simulation results show that the duration of the proposed training sequence is less than an OFDM symbol,and can be modified after evaluating the signal-to-noise ratio.Moreover,the proposed algorithm can still work when the normalized CFO is 12,which is far beyond the frequency tolerance of the crystal oscillator(±10-5).Besides,the proposed algorithm has a good synchronization performance in the additive Gaussian noise channel and multi-path fading channel,and its pipelined structure makes it easily be implemented in hardware.
Key words:  OFDM  timing synchronization  variable synchronization frame  training sequence  differential correlation