Maximum likelihood timing and carrier frequency offset estimation for OFDM systems with periodic preambles

Hung Dau Hsieh; Wen-Rong Wu

doi:10.1109/APCCAS.2006.342358

Maximum likelihood timing and carrier frequency offset estimation for OFDM systems with periodic preambles

Hung Dau Hsieh, Wen-Rong Wu

National Chiao Tung University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Timing offset (TO) and carrier frequency offset (CFO) are two common problems observed in OFDM systems. Maximum likelihood (ML) methods have been proposed for CFO estimation. The conventional ML estimates consider a pilot-assisted system, in which two identical preambles are repeatedly transmitted. In some applications, the preambles of an OFDM system are repeated more than two times. A typical example is the preambles of the IEEE802.11a/g wireless local area network (LAN) system. A ML CFO estimation method for the system was proposed recently; however, the method has to solve the roots of the derivative of the likelihood function, and the computational complexity is high. Also, the TO estimation problem is not considered. In this paper, new methods are developed for the TO and CFO estimation problems. Our method is simple and does not rely on the root-finding approach. Simulations show that while the performance of the proposed method is either equal to or better than the existing method, the computational complexity is much lower.

Original language	English
Title of host publication	APCCAS 2006 - 2006 IEEE Asia Pacific Conference on Circuits and Systems
Pages	1204-1207
Number of pages	4
DOIs	https://doi.org/10.1109/APCCAS.2006.342358
State	Published - 1 Dec 2006
Event	APCCAS 2006 - 2006 IEEE Asia Pacific Conference on Circuits and Systems - , Singapore Duration: 4 Dec 2006 → 6 Dec 2006

Publication series

Name	IEEE Asia-Pacific Conference on Circuits and Systems, Proceedings, APCCAS

Conference

Conference	APCCAS 2006 - 2006 IEEE Asia Pacific Conference on Circuits and Systems
Country	Singapore
Period	4/12/06 → 6/12/06

Keywords

Frequency offset
Maximum-likelihood (ML) estimation
Orthogonal frequency-division multiplexing (OFDM)
Timing offset

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title = "Maximum likelihood timing and carrier frequency offset estimation for OFDM systems with periodic preambles",

abstract = "Timing offset (TO) and carrier frequency offset (CFO) are two common problems observed in OFDM systems. Maximum likelihood (ML) methods have been proposed for CFO estimation. The conventional ML estimates consider a pilot-assisted system, in which two identical preambles are repeatedly transmitted. In some applications, the preambles of an OFDM system are repeated more than two times. A typical example is the preambles of the IEEE802.11a/g wireless local area network (LAN) system. A ML CFO estimation method for the system was proposed recently; however, the method has to solve the roots of the derivative of the likelihood function, and the computational complexity is high. Also, the TO estimation problem is not considered. In this paper, new methods are developed for the TO and CFO estimation problems. Our method is simple and does not rely on the root-finding approach. Simulations show that while the performance of the proposed method is either equal to or better than the existing method, the computational complexity is much lower.",

keywords = "Frequency offset, Maximum-likelihood (ML) estimation, Orthogonal frequency-division multiplexing (OFDM), Timing offset",

author = "Hsieh, {Hung Dau} and Wen-Rong Wu",

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Hsieh, HD & Wu, W-R 2006, Maximum likelihood timing and carrier frequency offset estimation for OFDM systems with periodic preambles. in APCCAS 2006 - 2006 IEEE Asia Pacific Conference on Circuits and Systems., 4145615, IEEE Asia-Pacific Conference on Circuits and Systems, Proceedings, APCCAS, pp. 1204-1207, APCCAS 2006 - 2006 IEEE Asia Pacific Conference on Circuits and Systems, Singapore, 4/12/06. https://doi.org/10.1109/APCCAS.2006.342358

Maximum likelihood timing and carrier frequency offset estimation for OFDM systems with periodic preambles. / Hsieh, Hung Dau; Wu, Wen-Rong.

APCCAS 2006 - 2006 IEEE Asia Pacific Conference on Circuits and Systems. 2006. p. 1204-1207 4145615 (IEEE Asia-Pacific Conference on Circuits and Systems, Proceedings, APCCAS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Wu, Wen-Rong

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N2 - Timing offset (TO) and carrier frequency offset (CFO) are two common problems observed in OFDM systems. Maximum likelihood (ML) methods have been proposed for CFO estimation. The conventional ML estimates consider a pilot-assisted system, in which two identical preambles are repeatedly transmitted. In some applications, the preambles of an OFDM system are repeated more than two times. A typical example is the preambles of the IEEE802.11a/g wireless local area network (LAN) system. A ML CFO estimation method for the system was proposed recently; however, the method has to solve the roots of the derivative of the likelihood function, and the computational complexity is high. Also, the TO estimation problem is not considered. In this paper, new methods are developed for the TO and CFO estimation problems. Our method is simple and does not rely on the root-finding approach. Simulations show that while the performance of the proposed method is either equal to or better than the existing method, the computational complexity is much lower.

AB - Timing offset (TO) and carrier frequency offset (CFO) are two common problems observed in OFDM systems. Maximum likelihood (ML) methods have been proposed for CFO estimation. The conventional ML estimates consider a pilot-assisted system, in which two identical preambles are repeatedly transmitted. In some applications, the preambles of an OFDM system are repeated more than two times. A typical example is the preambles of the IEEE802.11a/g wireless local area network (LAN) system. A ML CFO estimation method for the system was proposed recently; however, the method has to solve the roots of the derivative of the likelihood function, and the computational complexity is high. Also, the TO estimation problem is not considered. In this paper, new methods are developed for the TO and CFO estimation problems. Our method is simple and does not rely on the root-finding approach. Simulations show that while the performance of the proposed method is either equal to or better than the existing method, the computational complexity is much lower.

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