Blind equalization and automatic modulation classification based on PDF fitting

Souhaila Fki (1, 2) , Abdeldjalil Aissa El Bey (3, 1) , Thierry Chonavel (4, 1)

1 SC - Département Signal et Communications
2 Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
3 Lab-STICC_TB_CACS_COM
4 Lab-STICC_TB_CID_TOMS

In this paper, a completely blind equalizer based on probability density function (pdf) fitting is proposed. It doesn't require any prior information about the transmission channel or the emitted constellation. We also investigate Automatic Modulation Classification (AMC) for Quadrature Amplitude Modulation (QAM) based on the pdf of the equalized signal. We propose three new approaches for AMC. The first employs maximum likelihood functions (ML) of the modulus of real and imaginary parts of the equalized signal. The second is based on the lowest quadratic or Bhattacharyya distance between the estimated pdf of the real and imaginary parts of the equalizer output and the theoretical pdfs of M-QAM modulations. The third approach is based on theoretical pdf dictionnary learning. The performance of the identification scheme is investigated through simulations.

Mots clés: Blind equalization; AMC; Bhat- tacharyya distance

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

Souhaila Fki, Abdeldjalil Aissa El Bey, Thierry Chonavel. Blind equalization and automatic modulation classification based on PDF fitting. ICASSP 2015 : 40th IEEE International Conference on Acoustics, Speech and Signal Processing, Apr 2015, Brisbane, Australia. pp.2989 - 2993. ⟨hal-01188847⟩