… Existing techniques typically find near-optimal power allocations by solving a challenging …
power allocation scheme is developed based on model-free deep reinforcement learning. …

… -based power allocation … reinforcement learning (DRL) is regarded as one such approach
having great potential for future intelligent networks. In this paper, a dynamic downlink power …

… Similar to JRA, we derive an optimal power allocation given channel assignment. Then, with
the optimal power allocation, we propose to utilize the deep reinforcement learning to learn …

… Reinforcement learning techniques, such as Q-learning can derive the optimal strategy with
… a Q-learning based power allocation strategy that chooses the transmit power based on the …

… the handover (HO) and power allocation problem in a two-tier … We establish an HO
management and power allocation … ), we first model the HO and power allocation problem as a …

… In this paper, we investigate a joint device association, spectrum allocation, and power
allocation optimization problem in two-tier heterogeneous wireless networks. As the network is …

… In this paper, we explore two DRL power allocation methods, namely the deep Q-network
(… stated, the power allocation in this paper refers to the downlink power allocation. Although …

… objective of minimizing power … Reinforcement Learning (DRL) on solving complicated control
problems, we present a novel DRL-based framework for power-efficient resource allocation …

… Next, we introduce two reinforcement learning methods that are used in the proposed
design. Q-learning [11] is a popular reinforcement learning method that learns an action value …

… Abstract—In this paper, multi-cell power allocation approach is researched. Different from …
, Deep Reinforcement Learning (DRL) method is employed to solve the power allocation issue …