In our paper, we propose a two-step training framework. First, with the off-line learning in simulated environment, a deep Q network (DQN) is trained with deep ...

Jun 18, 2020 · The model-based power allocation has been investigated for decades, but this approach requires mathematical models to be analytically ...

Jan 22, 2019 · In this paper, the DRL approaches are considered for power control in multi-user wireless communication cellular networks.

Dec 7, 2018 · The Q learning method is the most well-studied RL algorithm, and it is exploited to cope with power allocation (PA) in [11]–[13], and some ...

A deep Q network (DQN) is trained with deep Q learning (DQL) algorithm, which is well-designed to be in consistent with this PA issue, and results show that ...

The model-driven power allocation (PA) algorithms in the wireless cellular networks with interfering multiple-access channel (IMAC) have been investigated ...

Through a trialand-error strategy, DRL algorithms utilize interactions between agents and environments to determine optimal policies for solving problems.

In this paper, we propose a novel centralized DRL based downlink power allocation scheme for a multi-cell system intending to maximize the total network ...

PA_TWC https://arxiv.org/abs/1901.07159 "Power Allocation in Multi-User Cellular Networks: Deep Reinforcement Learning Approaches"

A wireless resource mapping method and a deep neural network for multi-cell power allocation named as Deep-Q-Full-Connected-Network (DQFCNet) which can ...