… Abstract—We develop a framework based on deep reinforcement learning (DRL) to
solve the spectrum allocation problem in the emerging integrated access and backhaul (IAB) …

… performance through the Integrated access and backhaul (IAB… a novel approach leveraging
deep reinforcement learning (… but also maintains seamless integration with central network …

… using integrated access and backhaul (IAB) technology to provide coverage for users in the
disaster area. With the data collected from the system-level simulation, a deep reinforcement …

… This article proposes a radio resource management solution for congestion avoidance on
the access side of an integrated access and backhaul (IAB) network using deep reinforcement …

… Motivated by this, a more economical and sustainable solution, integrated access and
backhaul (IAB), has been proposed by the 3rd Generation Partnership Project (3GPP) [5], [6]. In …

… We investigate the use of Deep Reinforcement Learning, in particular, Deep Q … integrating
deep learning with Q learning, Deep Q learning or Deep Q Network (DQN) [5] can use a deep …

… design Deep Reinforcement Learning (DRL)-based optimizers with Deep Q-Network (DQN)
and Deep Deterministic Policy Gradients (DDPG) for optimizing RACH schemes, including …

… reinforcement learning problem. A distributed cooperative massive access approach based
on deep reinforcement … on URLLC services in massive access scenario. In addition, transfer …

… In this paper, the ambient energy harvesting is integrated with wireless local area network
(… their random access, namely ambient energy harvesting carrier-sense-multiple-access with …

… Deep actor-critic based reinforcement learning (RL) is used in this … The spectrum access
decision is modelled as a game where … Reinforcement learning (RL) and deep reinforcement …