Utilisation de l’Apprentissage par Renforcement pour le Green Networking dans un Réseau de Radio Cognitive

Abstract

The new concept "Green Networking" can take advantage of the broad paradigm of cognitive radio. The goal of our final master's project is to find a mechanism that minimizes energy consumption by integrating it into the cognitive radio network. For this, we used the algorithm of Q-Learning, a reinforcement learning technique that will help the cognitive user to find the optimal channel that has a low transmission power by guaranteeing the needs of his application, and therefore a reduction in battery consumption.

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