… a distributed learning algorithm for dynamic spectrum access that can … deep multiuser
reinforcement learning approach to achieve this goal. Deep reinforcement learning (DRL) (or deep …

… fair dynamic spectrum access in distributed wireless networks (DWNs). To limit the required
communication between nodes, several schemes based on reinforcement learning (RL) …

… spectrum access opportunities [3]. Hence, a concept of dynamic spectrum access (DSA) is
raised, where spectrum … DSA is an enabling and supporting technology for distributed Internet …

… DSA network under the presence of spectrum sensing errors. To be specific… deep reinforcement
learning (DRL), for SUs to learn “appropriate” spectrum access strategies in a distributed …

… distributed DSA network considering the physical layer parameters of the network that
dynamically optimize the resources for spectrum access … Andrews, “A deep reinforcement learning …

… such distributed circumstances, intelligent dynamic spectrum … self-learning to achieve dynamic
spectrum access improvement. … on deep reinforcement learning to enhance spectrum and …

… Deep reinforcement learning (DRL) [9] embraces the multidimensional perception ability of
deep … 3) We propose a multiuser distributed spectrum access algorithm based on cooperative …

… deep Q-learning originated spectrum access … Spectrum Allocation (DESA) and Centralized
Spectrum Allocation (CSA), respectively. Actions that are generated through centralized deep …

… In this paper, we consider a dynamic spectrum access scenario with a mesh network of
2N primary radio nodes including N transmitters and N receivers. The N primary transmitters …

… In this work, we consider a dynamic spectrum access environment where N nodes
dynamically choose to transmit on one of K channels. At the beginning of each time step, some …