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Adaptive Joint Semi-blind Estimation of CFO and Channel for OFDM Systems

Mokhtar Besseghier Ahmed Bouzidi Djebbar Iyad Dayoub 1, 2 
2 COMNUM - IEMN - COMmunications NUMériques - IEMN
IEMN-DOAE - Institut d’Électronique, de Microélectronique et de Nanotechnologie - Département Opto-Acousto-Électronique - UMR 8520
Abstract : The large number of subcarriers, used in OFDM systems, increases the sensivity to frequency offset which results from a Doppler shift, due to mobile movement, as well as from a mismatch between the carrier frequencies at the transmitter and receiver. The problem of channel estimation in a practical OFDM receiver that suffers from CFO has been addressed in this paper. We first derived the modified MUSIC based blind CFO estimator. Next, we propose new joint training-based and joint semi-blind CFO and channel estimation for OFDM systems. Whereas the training-based estimator only assumes knowledge of pilot tones, the semi-blind estimator assumes knowledge of the virtual subcarriers (VSCs). For both estimators we derive a maximum likelihood (ML) algorithm for block processing and LMS algorithm for adaptive processing. It is demonstrated that the CFO estimators are able to perform well with a very small number of OFDM blocks. The performance of our estimators was investigated by simulations.
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https://hal-uphf.archives-ouvertes.fr/hal-03383003
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Submitted on : Monday, October 18, 2021 - 1:55:53 PM
Last modification on : Wednesday, March 23, 2022 - 3:51:16 PM

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Mokhtar Besseghier, Ahmed Bouzidi Djebbar, Iyad Dayoub. Adaptive Joint Semi-blind Estimation of CFO and Channel for OFDM Systems. Wireless Personal Communications, Springer Verlag, 2015, 81 (2), pp.473-487. ⟨10.1007/s11277-014-2139-7⟩. ⟨hal-03383003⟩

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