Signal detection through circular convolution reconstruction for OFDM system in fast varying channel
A signal detection algorithm is proposed for the orthogonal frequency division multiplexing (OFDM) system in the presence of fast time-varying channel. The channel is represented by a piece-wise linear variant model with normalized Doppler frequency of less than 0.2. The channel parameters are extracted through ISI/ICI (inter-symbol interference/ inter-carrier interference) cancellation and circular convolution reconstruction. Meanwhile, an improved OFDM symbol detection algorithm is also proposed based on circular convolution reconstruction. The channel state information in the OFDM symbol duration can be obtained accurately from the adjacent two block pilots in a linear model. The simulation results show that the proposed method can not only track the channel variation, but also promise better performance gain in the OFDM symbol detection. Furthermore, the bit error ratio (BER) is close to the performance with the perfect channel state information.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/2095087X
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Supplemental Notes:
- Copyright © 2012 Journal of Modern Transportation
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Authors:
- Zuo, Hai
- Lei, Xia
- Le, Rongzhen
- Jin, Maozhu
- Publication Date: 2012
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; References; Tables;
- Pagination: pp 234-242
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Serial:
- Journal of Modern Transportation
- Volume: 20
- Issue Number: 4
- Publisher: Springer Verlag
- ISSN: 2095-087X
- Serial URL: http://jmt.swjtu.edu.cn/EN/volumn/home.shtml
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Publication flags:
Open Access (libre)
Subject/Index Terms
- TRT Terms: Algorithms; Detection and identification; Doppler effect; Wireless communication systems
- Uncontrolled Terms: High definition television; Signal detection
- Geographic Terms: China
- Subject Areas: Data and Information Technology; Highways; Railroads; I70: Traffic and Transport;
Filing Info
- Accession Number: 01487645
- Record Type: Publication
- Files: TRIS
- Created Date: Jul 2 2013 11:01AM