Deep learning based online power control for large energy harvesting networks
In this paper, we propose a deep learning based approach to design online power control
policies for large EH networks, which are often intractable stochastic control problems. In the …
policies for large EH networks, which are often intractable stochastic control problems. In the …
Multi-agent deep reinforcement learning based power control for large energy harvesting networks
The goal in this work is to design online power control policies for large energy harvesting
(EH) networks where, due to large energy overhead involved in the exchange of state …
(EH) networks where, due to large energy overhead involved in the exchange of state …
Distributed power control for large energy harvesting networks: A multi-agent deep reinforcement learning approach
In this paper, we develop a multi-agent reinforcement learning (MARL) framework to obtain
online power control policies for a large energy harvesting (EH) multiple access channel …
online power control policies for a large energy harvesting (EH) multiple access channel …
Optimal stochastic power control for energy harvesting systems with delay constraints
This paper studies stochastic power control problems over a fading channel, where the
transmitter randomly harvests renewable energies from environment and stores them in a …
transmitter randomly harvests renewable energies from environment and stores them in a …
Joint EH time and transmit power optimization based on DDPG for EH communications
L Li, H Xu, J Ma, A Zhou, J Liu - IEEE Communications Letters, 2020 - ieeexplore.ieee.org
Energy management and power allocation policy is considered for energy harvesting (EH)
communications. In this letter, we propose a joint optimization problem with the continuous …
communications. In this letter, we propose a joint optimization problem with the continuous …
Deep deterministic policy gradient based dynamic power control for self-powered ultra-dense networks
H Li, T Lv, X Zhang - 2018 IEEE Globecom Workshops (GC …, 2018 - ieeexplore.ieee.org
By densely deploying the base stations (BSs), Ultra Dense Network (UDN) exhibits strong
potential to enhance the network capacity, while leading to huge power consumption and a …
potential to enhance the network capacity, while leading to huge power consumption and a …
Power control in energy harvesting multiple access system with reinforcement learning
The Internet of Things (IoT) application has a crucial need for long-term and self-sustainable
operations. Energy harvesting (EH) technique has attracted great attention in IoT as it may …
operations. Energy harvesting (EH) technique has attracted great attention in IoT as it may …
Action-bounding for reinforcement learning in energy harvesting communication systems
In this paper, we consider a power allocation problem for energy harvesting communication
systems, where a transmitter wants to send the desired messages to the receiver with the …
systems, where a transmitter wants to send the desired messages to the receiver with the …
Fast-convergent learning-aided control in energy harvesting networks
L Huang - IEEE Transactions on Mobile Computing, 2019 - ieeexplore.ieee.org
In this paper, we present a novel learning-aided energy management scheme (LEN) for
multihop energy harvesting networks. Different from prior works on this problem, our …
multihop energy harvesting networks. Different from prior works on this problem, our …
On the design of tailored neural networks for energy harvesting broadcast channels: A reinforcement learning approach
In this paper, we consider a power allocation optimization technique for a time-varying
fading broadcast channel in energy harvesting communication systems, in which a …
fading broadcast channel in energy harvesting communication systems, in which a …