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

… the agent and the broadcasting allocation scheme to each transmitter becomes challenging.
Therefore, we propose to decentralize the power allocation scheme. The transmitter of each …

… Then, with the optimal power allocation, we propose to utilize the deep reinforcement
learning to learn an optimal channel assignment policy. To capture the sequential relations …

… 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, the power allocation of a base station in a NOMA system equipped with multiple
antennas contending with a smart jammer is formulated as a zero-sum game, in which the …

… 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 …

… the handover (HO) and power allocation problem in a two-tier … HO management and power
allocation scheme to maximize … we first model the HO and power allocation problem as a fully …

… Reinforcement learning (RL) is regarded as a promising tool for resource management in
femtocell networks. In this work, power allocation is modeled as a Markov Decision Process …

… with various CSI exchange schemes in multi-user multi-cell … We propose a deep reinforcement
learning (DRL) framework … where P(c) k,[t] denotes the power allocated on RB c of SBS …

… Researches [16], [17] find the optimal channel assignment with fixed power allocation, …
scheme, we introduce reinforcement learning to optimize dynamic power and channel allocation …