NDLI: A General Carrier Frequency Offset Estimator for Broadband OFDM

Content Provider	IEEE Xplore Digital Library
Author	Defeng Huang Letaief, K.B.
Copyright Year	2005
Description	Author affiliation: Dept. of Electron. Eng., Tsinghua Univ., Beijing (Defeng Huang)
Abstract	OFDM (orthogonal frequency division multiplexing) is a promising technology for future broadband wireless communications due to its capability in combating multipath fading. Carrier frequency offset (CFO), which can induce the loss of orthogonality among OFDM sub-carriers and significant performance degradation, needs to be estimated and compensated for. In this paper, we propose a general CFO estimator based on the maximum likelihood (ML) estimation criterion. It will be shown that with the same estimator architecture, CFO can be obtained using either training OFDM symbols, pilot tones, null sub-carriers, or a combination of them. Furthermore, by taking advantage of the channel side information, the performance of CFO estimation can be significantly improved. To demonstrate the capability of the proposed CFO estimator, we will consider an OFDM system using the signal structure of the IEEE WLAN standard 802.11a. Compared with previous work using null sub-carriers alone, it will be shown that by taking advantage of the pilot tones, null sub-carriers, and the channel statistics, the performance of CFO estimation can be improved by about 2 dB
Starting Page	1083
Ending Page	1087
File Size	244228
Page Count	5
File Format	PDF
ISBN	0780391322
DOI	10.1109/APCC.2005.1554231
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-10-05
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Frequency estimation OFDM Maximum likelihood estimation Broadband communication Wireless communication Fading Performance loss Degradation Wireless LAN Statistics null sub-carrier Carrier frequency offset IEEE 802.11a
Content Type	Text
Resource Type	Article

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