New Structure of CCR with an AOANN Threshold - Université Polytechnique des Hauts-de-France Accéder directement au contenu
Article Dans Une Revue Journal of Optical Communications and Networking Année : 2021

New Structure of CCR with an AOANN Threshold

Abdelhalim Rabehi
  • Fonction : Auteur
Ali Djebbari
  • Fonction : Auteur
Ahmed Hafaifa
  • Fonction : Auteur
  • PersonId : 1048087
Abdelkerim Souahlia
  • Fonction : Auteur

Résumé

In this paper, artificial neural network-based adaptive optimal threshold estimation for a two-dimensional optical code division multiple access conventional correlation receiver is proposed. A multilayer perceptron neural network with back-propagation learning algorithm is considered. This estimator uses the weight ( w ) and the length ( F ) of the code word, the number of active users ( Ν ) and the signal to noise ratio as inputs to estimate the required optimal threshold. We have evaluated the proposed approach on a data set of 46,200 samples. We have found that it gives accurate results: 0.029 for the root mean square error, 0.37% for the relative root mean square error and 99.984% for the correlation coefficient (R), which reflects the efficiency of the proposed optimal threshold estimator.
Fichier non déposé

Dates et versions

hal-03718064 , version 1 (08-07-2022)

Identifiants

Citer

Abdelhalim Rabehi, Ali Djebbari, Ahmed Hafaifa, Abdelkerim Souahlia, Abdelmalik Taleb-Ahmed. New Structure of CCR with an AOANN Threshold. Journal of Optical Communications and Networking, 2021, 42 (1), pp.103-109. ⟨10.1515/joc-2018-0028⟩. ⟨hal-03718064⟩
5 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More