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Two symbol timing estimation methods using Barker and Kasami sequence as preamble for OFDM-based WLAN systems

机译:使用Barker和Kasami序列作为基于OFDM的WLAN系统的前同步码的两种符号定时估计方法

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The estimation of the exact point for the start of the symbol is significant as the orthogonal frequency division multiplexing (OFDM) systems are very sensitive to timing errors. In the IEEE 802.11a wireless local area network (WLAN), each data packet starts with a preamble consisting of ten short training symbols followed by two long training symbols. The timing metric is computed through autocorrelation of the received samples and their delayed copies. When the preambles are known to the receiver, the timing metric is obtained by crosscorrelation of the received samples with the locally generated samples. The correlation peak of the timing metric indicates the correct symbol time. The symbol timing synchronization schemes in IEEE 802.11a WLAN systems use short training symbols to estimate a coarse symbol time via autocorrelation and then use long symbols to find a fine symbol time via crosscorrelation. In this paper, Barker and Kasami codes are proposed to be used as preambles for timing estimation in OFDM WLAN systems. Timing estimation makes use of correlation of preamble. So preamble with good autocorrelation property has to be chosen. The proposed scheme develops a simple preamble structure and gives more accurate estimate of symbol timing.
机译:由于正交频分复用(OFDM)系统对定时误差非常敏感,因此对于符号开始的精确点的估计非常重要。在IEEE 802.11a无线局域网(WLAN)中,每个数据包均以一个前导开头,该前导由十个短训练符号和两个长训练符号组成。通过接收样本及其延迟副本的自相关来计算时序度量。当接收器知道前同步码时,通过将接收到的样本与本地生成的样本进行互相关来获得时序度量。时序度量的相关峰指示正确的符号时间。 IEEE 802.11a WLAN系统中的符号定时同步方案使用短训练符号通过自相关来估计粗略的符号时间,然后使用长符号通过互相关来找到细的符号时间。本文提出将Barker和Kasami码用作OFDM WLAN系统中时序估计的前同步码。时序估计利用前同步码的相关性。因此,必须选择具有良好自相关特性的前导码。所提出的方案开发了简单的前同步码结构,并且给出了符号定时的更准确的估计。

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