Analysis of the Maximum-likelihood Channel Estimator for OFDM Systems with Unknown Interference

Azzouz Dermoune (1) , Eric Pierre Simon (2)

1 LPP - Laboratoire Paul Painlevé - UMR 8524
2 TELICE - IEMN - Télécommunication, Interférences et Compatibilité Electromagnétique - IEMN

—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.

Mots clés: OFDM; interference; channel; estimation; cognitive-radio

Domaines: Traitement du signal et de l'image [eess.SP]

Azzouz Dermoune, Eric Pierre Simon. Analysis of the Maximum-likelihood Channel Estimator for OFDM Systems with Unknown Interference. 2015. ⟨hal-01169591⟩