Deep reinforcement learning-assisted energy harvesting wireless networks

J Ye, H Gharavi - IEEE transactions on green communications …, 2020 - ieeexplore.ieee.org
Heterogeneous ultra-dense networking (HUDN) with energy harvesting technology is a
promising approach to deal with the ever-growing traffic that can severely impact the power …

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 …

Deep Q-learning based dynamic resource allocation for self-powered ultra-dense networks

H Li, H Gao, T Lv, Y Lu - 2018 IEEE International Conference …, 2018 - ieeexplore.ieee.org
Though enhancing the capacity and coverage of cellular networks to meet the explosive
increasing of traffic demands, Ultra-Dense Network (UDN) suffers from great power …

Deep deterministic policy gradient (DDPG)-based energy harvesting wireless communications

C Qiu, Y Hu, Y Chen, B Zeng - IEEE Internet of Things Journal, 2019 - ieeexplore.ieee.org
To overcome the difficulties of charging the wireless sensors in the wild with conventional
energy supply, more and more researchers have focused on the sensor networks with …

Throughput maximization by deep reinforcement learning with energy cooperation for renewable ultradense IoT networks

Y Li, X Zhao, H Liang - IEEE Internet of Things Journal, 2020 - ieeexplore.ieee.org
Ultradense network (UDN) is considered as one of the key technologies for the explosive
growth of mobile traffic demand on the Internet of Things (IoT). It enhances network capacity …

Cooperative reinforcement learning based throughput optimization in energy harvesting wireless sensor networks

Y Wu, K Yang - 2018 27th Wireless and Optical Communication …, 2018 - ieeexplore.ieee.org
Energy Harvesting-Wireless Sensor Network (EH-WSN) has got increasing attention in
recent years. During its actual deployment, we find that the energy which can be harvested …

Reinforcement learning for energy harvesting decode-and-forward two-hop communications

A Ortiz, H Al-Shatri, X Li, T Weber… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Energy harvesting (EH) two-hop communications are considered. The transmitter and the
relay harvest energy from the environment and use it exclusively for transmitting data. A data …

Radio and energy resource management in renewable energy-powered wireless networks with deep reinforcement learning

HS Lee, DY Kim, JW Lee - IEEE Transactions on Wireless …, 2022 - ieeexplore.ieee.org
In this paper, we study radio and energy resource management in renewable energy-
powered wireless networks, where base stations (BSs) are powered by both on-grid and …

Deep reinforcement learning aided intelligent access control in energy harvesting based WLAN

Y Zhao, J Hu, K Yang, S Cui - IEEE Transactions on Vehicular …, 2020 - ieeexplore.ieee.org
The increasing number of low power communication devices in the era of Internet of Things
(IoT) has resulted in challenges in maintenance and continuous energy supply. In this …

Energy-efficient power allocation and user association in heterogeneous networks with deep reinforcement learning

CK Hsieh, KL Chan, FT Chien - Applied Sciences, 2021 - mdpi.com
This paper studies the problem of joint power allocation and user association in wireless
heterogeneous networks (HetNets) with a deep reinforcement learning (DRL)-based …