A Novel Timing Estimation Method Using Symmetry Characteristic in BPSK-OFDM Symbol

碩士 === 國立中正大學 === 電機工程研究所 === 93 === Recently, the modulation techniques which can provide a broadband transmission over wireless channels are widely discussed. Because the multimedia is becoming more and more necessitated, to employ with useful bandwidth perfectly and to raise the data rate are nec...

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Bibliographic Details
Main Authors: Wen-Hui Kuan, 官雯彗
Other Authors: Jyh-Horng Wen
Format: Others
Language:en_US
Published: 2005
Online Access:http://ndltd.ncl.edu.tw/handle/80256655713140659690
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Summary:碩士 === 國立中正大學 === 電機工程研究所 === 93 === Recently, the modulation techniques which can provide a broadband transmission over wireless channels are widely discussed. Because the multimedia is becoming more and more necessitated, to employ with useful bandwidth perfectly and to raise the data rate are necessary. OFDM is a technique which has number of sub-carriers to modulate. To use the orthogonality between different sub-carriers, OFDM systems can employ with useful bandwidth perfectly. Because the guard interval is added in each OFDM symbol, the inter-symbol interference can be solved effectively. In this thesis, to use the symmetry characteristic in a BPSK-OFDM symbol in time domain, two algorithms for timing synchronization in BPSK-OFDM systems are presented. The first algorithm employs the variance in the phase of the multiplication with the opposite samples, and the second one employs the correlation between the opposite samples. Through the simulation results, the efficiency in both proposed algorithms will be demonstrated. Because of using the symmetry characteristic between opposite samples to estimate symbol timing, the performance has a clear minimum or maximum point (dependent on algorithm 1 or algorithm 2) appeared on the actual symbol timing. Therefore, the actual symbol timing can be easily obtained. Although the proposed algorithm 1 has more complex than algorithm 2, it has better performance than algorithm 2 when signal-to-noise ratio is large while it has worse performance than algorithm 2 when signal-to-noise ratio is small.