DocumentCode
979632
Title
Optimal periodic training signal for frequency offset estimation in frequency-selective fading channels
Author
Minn, Hlaing ; Fu, Xiaoyu ; Bhargava, Vijay K.
Author_Institution
Dept. of Electr. Eng., Texas Univ., Richardson, TX
Volume
54
Issue
6
fYear
2006
fDate
6/1/2006 12:00:00 AM
Firstpage
1081
Lastpage
1096
Abstract
This paper addresses an optimal periodic training signal design for frequency offset estimation in frequency-selective multipath Rayleigh fading channels. For a fixed transmitted training signal energy within a fixed-length block, the optimal periodic training signal structure (the optimal locations of identical training subblocks) and the optimal training subblock signal are presented. The optimality is based on the minimum Cramer-Rao bound (CRB) criterion. Based on the CRB for joint estimation of frequency offset and channel, the optimal periodic training structure (optimality only in frequency offset estimation, not necessarily in joint frequency offset and channel estimation) is derived. The optimal training subblock signal is obtained by using the average CRB (averaged over the channel fading) and the received training signal statistics. A robust training structure design is also presented in order to reduce the occurrence of outliers at low signal-to-noise ratio values. The proposed training structures and subblock signals achieve substantial performance improvement
Keywords
Rayleigh channels; channel estimation; frequency estimation; signal processing; statistics; Cramer-Rao bound criterion; Rayleigh fading channels; channel estimation; fixed-length block; frequency offset estimation; frequency-selective fading channels; optimal periodic training signal; optimal training subblock signal; signal-to-noise ratio; training signal statistics; AWGN; Autocorrelation; Channel estimation; Frequency estimation; Frequency synchronization; Frequency-selective fading channels; Minimax techniques; Periodic structures; Signal design; Timing; Cramer–Rao bound (CRB); frequency offset estimation; training signal design; training structure; zero autocorrelation (ZAC);
fLanguage
English
Journal_Title
Communications, IEEE Transactions on
Publisher
ieee
ISSN
0090-6778
Type
jour
DOI
10.1109/TCOMM.2006.876869
Filename
1643537
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