Open AccessRobust and Efficient Frequency Estimator for Undersampled Waveforms Based on Frequency Offset Recognition
Author(s) -
Xiangdong Huang,
Ruipeng Bai,
Xukang Jin,
Haipeng Fu
Publication year - 2016
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0163871
Subject(s) - estimator , remainder , frequency offset , offset (computer science) , robustness (evolution) , computer science , carrier frequency offset , algorithm , chinese remainder theorem , signal to noise ratio (imaging) , mathematics , statistics , telecommunications , orthogonal frequency division multiplexing , biochemistry , chemistry , arithmetic , gene , programming language
This paper proposes an efficient frequency estimator based on Chinese Remainder Theorem for undersampled waveforms. Due to the emphasis on frequency offset recognition (i.e., frequency shift and compensation) of small-point DFT remainders, compared to estimators using large-point DFT remainders, it can achieve higher noise robustness in low signal-to-noise ratio (SNR) cases and higher accuracy in high SNR cases. Numerical results show that, by incorporating a remainder screening method and the Tsui spectrum corrector, the proposed estimator not only lowers the SNR threshold of detection, but also provides a higher accuracy than the large-point DFT estimator when the DFT size decreases to 1/90 of the latter case.