Analysis of the Maximum-likelihood Channel ...
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Title :
Analysis of the Maximum-likelihood Channel Estimator for OFDM Systems with Unknown Interference
Author(s) :
Dermoune, Azzouz [Auteur]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Simon, Eric [Auteur]
Télécommunication, Interférences et Compatibilité Electromagnétique - IEMN [TELICE - IEMN]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Simon, Eric [Auteur]

Télécommunication, Interférences et Compatibilité Electromagnétique - IEMN [TELICE - IEMN]
English keyword(s) :
OFDM
interference
channel
estimation
cognitive-radio
interference
channel
estimation
cognitive-radio
HAL domain(s) :
Sciences de l'ingénieur [physics]/Traitement du signal et de l'image [eess.SP]
English abstract : [en]
—In this paper, a comprehensive theoretical analysis of the maximum-likelihood (ML) channel estimator for OFDM systems with unknown interference is presented. The uniqueness of the solution is analytically demonstrated ...
Show more >—In this paper, a comprehensive theoretical analysis of the maximum-likelihood (ML) channel estimator for OFDM systems with unknown interference is presented. The uniqueness of the solution is analytically demonstrated when the number of transmitted OFDM symbols is strictly greater than one. This solution is derived from the iterative conditional ML (CML) algorithm. It is shown that the channel estimate can be described as an algebraic function whose inputs are the initial value and the means and variances of the received samples. It is also theoretically demonstrated that the channel estimator is not biased, and that the second moment exists as long as the number of transmitted OFDM symbols is strictly greater than three. Furthermore, this is confirmed by numerical results.Show less >
Show more >—In this paper, a comprehensive theoretical analysis of the maximum-likelihood (ML) channel estimator for OFDM systems with unknown interference is presented. The uniqueness of the solution is analytically demonstrated when the number of transmitted OFDM symbols is strictly greater than one. This solution is derived from the iterative conditional ML (CML) algorithm. It is shown that the channel estimate can be described as an algebraic function whose inputs are the initial value and the means and variances of the received samples. It is also theoretically demonstrated that the channel estimator is not biased, and that the second moment exists as long as the number of transmitted OFDM symbols is strictly greater than three. Furthermore, this is confirmed by numerical results.Show less >
Language :
Anglais
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Submission date :
2025-01-24T18:22:27Z
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