Research Article
A Novel ML-Based Frequency Offset Estimator for OFDM Systems
@INPROCEEDINGS{10.1109/ChinaCom.2011.6158203, author={Han Jiang and Minjian Zhao and Jie Zhong and Yunlong Cai and Hao Wu}, title={A Novel ML-Based Frequency Offset Estimator for OFDM Systems}, proceedings={6th International ICST Conference on Communications and Networking in China}, publisher={IEEE}, proceedings_a={CHINACOM}, year={2012}, month={3}, keywords={carrier frequency offset estimation orthogonal frequency division multiplexing (ofdm) maximum-likelihood (ml) estimate}, doi={10.1109/ChinaCom.2011.6158203} }- Han Jiang
Minjian Zhao
Jie Zhong
Yunlong Cai
Hao Wu
Year: 2012
A Novel ML-Based Frequency Offset Estimator for OFDM Systems
CHINACOM
IEEE
DOI: 10.1109/ChinaCom.2011.6158203
Abstract
A novel carrier frequency offset (CFO) estimation algorithm based on the maximum-likelihood (ML) criterion for orthogonal frequency division multiplexing (OFDM) systems is proposed. In the proposed method, a well-known preamble with excellent timing synchronization is modified, and based on the improved preamble three fractional frequency offset estimators are investigated. The estimation range and the mean-square-error (MSE) performance under various signal-to-noise ratios (SNR) of the estimators are discussed. Finally, our proposed estimators are compared with the traditional Schmidl (SC) algorithm in terms of MSE. Simulation results demonstrate that the proposed methods have better performance than the SC frequency offset estimation algorithm in AWGN and multipath fading channels without increasing complexity. Moreover, the special characteristics of the improved preamble lead to a superior timing performance.