… In this paper, a novel deep reinforcement learning based dynamic channel allocation (DRL-DCA)
algorithm is proposed in multibeam satellite systems. Simulation result demonstrates …

… channels in the multi-carrier NOMA system is still unclear. In this paper, we propose a deep
reinforcement learning framework to allocate … to perform the channel assignment. Simulation …

… the dynamic channel allocation problem in SIoT as a Markov decision process (MDP).
We then propose a deep reinforcement learning algorithm for optimal channel allocation. To …

… In this work, we consider channel allocation among vehicles with various mobility rates as
a … In Section IV, we present proposed deep RL based mobility aware channel allocation. …

… ABSTRACT For densely deployed wireless local area networks (WLANs), this paper proposes
a deep reinforcement learning-based channel allocation scheme that enables the efficient …

… allocation of channels is … allocation of channels plays an important role in such systems.
In this paper, we propose a dynamic channel allocation scheme based on deep reinforcement …

… channel allocation method based on deep reinforcement learning (DRL), which is called
CA-DRL. CADRL develops a novel representation for the channel allocation … smart allocation …

… deep reinforcement learning (RL) for control problems containing large state space
dimensionality. In particular, a deep RL approach is explored for the problem of allocating … channel …

… Recently, the data-driven model-free approaches have been rapidly developed to achieve
near-optimal performance with affordable computational complexity, and deep reinforcement …

… APPLICATION OF DRLF In this section, we show the application of DRLF for a specific
use case of dynamic channel allocation (DCA) problem. DCA optimization problem in MBS …