Application of deep neural network and deep reinforcement learning in wireless communication.

ABSTRACT: OBJECTIVE:To explore the application of deep neural networks (DNNs) and deep reinforcement learning (DRL) in wireless communication and accelerate the development of the wireless communication industry. METHOD:This study proposes a simple cognitive radio scenario consisting of only one primary user and one secondary user. The secondary user attempts to share spectrum resources with the primary user. An intelligent power algorithm model based on DNNs and DRL is constructed. Then, the MATLAB platform is utilized to simulate the model. RESULTS:In the performance analysis of the algorithm model under different strategies, it is found that the second power control strategy is more conservative than the first. In the loss function, the second power control strategy has experienced more iteration

SUBMITTER: Li M 

PROVIDER: S-EPMC7332070 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature