Unsupervised deep learning to solve power allocation problems in cognitive relay networks - Archive ouverte HAL Accéder directement au contenu
Pré-Publication, Document De Travail Année : 2022

Unsupervised deep learning to solve power allocation problems in cognitive relay networks

Résumé

In this paper, an unsupervised deep learning approach is proposed to solve the constrained and non-convex Shannon rate maximization problem in a relay-aided cognitive radio network. This network consists of a primary and a secondary user-destination pair and a secondary full-duplex relay performing Decode-and-Forward. The primary communication is protected by a Quality of Service (QoS) constraint in terms of tolerated Shannon rate degradation. The relaying operation leads to non-convex objective and primary QoS constraint, which makes deep learning approaches relevant and promising. For this, we propose a fully-connected neural network architecture coupled with a custom and communication-tailored loss function to be minimized during training in an unsupervised manner. A major interest of our approach is that the required training data contains only system parameters without the corresponding solutions to the non-convex optimization problem, as opposed to supervised approaches. Our numerical experiments show that our proposed approach has a high generalization capability on unseen data without overfitting. Also, the predicted solution performs close to the brute force one, highlighting the high potential of our unsupervised approach.
Fichier principal
Vignette du fichier
Unsupervised_deep_learning_to_solve_power_allocation_problems_in_cognitive_relay_networks__ICC_ .pdf (1007.99 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03534545 , version 1 (19-01-2022)
hal-03534545 , version 2 (07-03-2022)
hal-03534545 , version 3 (10-03-2022)
hal-03534545 , version 4 (15-03-2022)

Identifiants

  • HAL Id : hal-03534545 , version 1

Citer

Yacine Benatia, Anne Savard, Romain Negrel, Elena Veronica Belmega. Unsupervised deep learning to solve power allocation problems in cognitive relay networks. 2022. ⟨hal-03534545v1⟩
200 Consultations
481 Téléchargements

Partager

Gmail Facebook X LinkedIn More