JOURNAL ARTICLE

Blind Estimation of OFDM Carrier Frequency Offset via Oversampling

B. ChenHui Wang

Year: 2004 Journal:   IEEE Transactions on Signal Processing Vol: 52 (7)Pages: 2047-2057   Publisher: Institute of Electrical and Electronics Engineers

Abstract

Blind deterministic estimation of the orthogonal frequency division multiplexing (OFDM) frequency offset via oversampling is proposed in this paper. This method utilizes the intrinsic phase shift of neighboring sample points incurred by the frequency offset that is common among all subcarriers. The proposed method is data efficient - it requires only a single OFDM symbol to achieve reliable estimation, hence making it more suitable to systems with stringent delay requirement and mobility-induced channel variation. The proposed scheme is devised to perfectly retrieve frequency offset in the absence of noise. Quite remarkably, we show that in the presence of channel noise, this intuitive scheme is indeed the maximum likelihood estimate of the carrier frequency offset. The possible presence of virtual carriers are also accommodated in the system model, and some interesting observations are obtained. The Cramer-Rao lower bound is derived for the oversampling-based signal model, and we show through numerical simulation that the proposed algorithm is efficient. Practical issues such as identifiability, the front-end filter bandwidth, and the possible presence of correlated noises are also carefully addressed.

Keywords:
Oversampling Orthogonal frequency-division multiplexing Carrier frequency offset Frequency offset Computer science Algorithm Phase noise Identifiability Subcarrier Offset (computer science) Cramér–Rao bound Bandwidth (computing) Electronic engineering Channel (broadcasting) Estimation theory Telecommunications Engineering

Metrics

100
Cited By
7.97
FWCI (Field Weighted Citation Impact)
23
Refs
0.98
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Wireless Communication Techniques
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Blind Source Separation Techniques
Physical Sciences →  Computer Science →  Signal Processing
PAPR reduction in OFDM
Physical Sciences →  Engineering →  Electrical and Electronic Engineering

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