… wireless communications have obtained widespread attention, among which deep reinforcement
… in enhancing the intelligence of wireless communication systems while overcoming the …

… deep reinforcement … deep reinforcement learning (DRL). A DRLbased framework is proposed
to tackle the non-convexity induced by the unit modulus constraints. We introduce the deep …

… show that the DQL can be used for the rate control to achieve multiple objectives in complex
communication systems. The network model is a future space communication system which …

… system services and resources, the agent of a network entity … With the uncertainties of mobile
communication systems as … actions are taken with the same system states. In this case, the Q…

… Deep reinforcement learning for spectrum sharing in future mobile communication system.
In … Systems and Broadcasting (BMSB), Chengdu, China, 4–6 August 2021. [Google Scholar] …

… -to-Infrastructure communication scenario. Using the recent advances in training deep neural
networks, we present a deep reinforcement learning model, namely deep Q-network, that …

… We consider an emergency communication system including an MBS, L UAV groups, and
K dynamic users. We assume the users are far from the MBS and there is no direct link. Hence…

… DRL to wireless communication networks. An intelligent power algorithm model based on
deep neural networks (… ideas for the later development of the wireless communication field. …

… Abstract—In this paper, we study an intelligent reflecting surface (IRS)-aided wireless secure
communication system, where an IRS is deployed to adjust its reflecting elements to secure …

… services. Based on the framework, we then apply deep reinforcement learning (DRL) into the
system … of multiobjective reinforcement learning and multiagent reinforcement learning are …