Multi-agent reinforcement-learning-based time-slotted channel hopping medium access control scheduling scheme

H Park, H Kim, ST Kim, P Mah - IEEE Access, 2020 - ieeexplore.ieee.org
Time-slotted channel hopping (TSCH) is a medium access control technology that realizes
collision-free wireless network communication by coordinating the media access time and …

The analysis of node planning and control logic optimization of 5G wireless networks under deep mapping learning algorithms

Z Han, J Liang - IEEE Access, 2019 - ieeexplore.ieee.org
In order to meet the needs of blowout growth of data flow and 10-100 times increase of user
experience rate, the next generation mobile communication (5G) heterogeneous network …

An actor-critic-based UAV-BSs deployment method for dynamic environments

Z Chen, Y Zhong, X Ge, Y Mia - ICC 2020-2020 IEEE …, 2020 - ieeexplore.ieee.org
In this paper, the real-time deployment of unmanned aerial vehicles (UAVs) as flying base
stations (BSs) for optimizing the throughput of mobile users is investigated for UAV networks …

A continuous actor–critic deep Q-learning-enabled deployment of UAV base stations: Toward 6G small cells in the skies of smart cities

N Parvaresh, B Kantarci - IEEE Open Journal of the …, 2023 - ieeexplore.ieee.org
Uncrewed aerial vehicle-mounted base stations (UAV-BSs), also know as drone base
stations, are considered to have promising potential to tackle the limitations of ground base …

Learning driven mobility control of airborne base stations in emergency networks

R Li, C Zhang, P Patras, R Stanica… - ACM SIGMETRICS …, 2019 - dl.acm.org
Mobile base stations mounted on unmanned aerial vehicles (UAVs) provide viable wireless
coverage solutions in challenging landscapes and conditions, where cellular/WiFi …

Proactive load balancing through constrained policy optimization for ultra-dense networks

M Huang, J Chen - IEEE Communications Letters, 2022 - ieeexplore.ieee.org
Designing an intelligent self-organizing network (SON) architecture is challenging for future
wireless networks. To meet the needs of SON, the reactive self-organizing model of the …

Joint Delay-Energy Optimization for Multi-Priority Random Access in Machine-Type Communications

W Fan, P Fan, Y Long - IEEE Transactions on Wireless …, 2023 - ieeexplore.ieee.org
Cellular-based networks are deemed as one solution to provide communication links for the
internet of things (IoT) due to its high reliability and wide coverage. However, due to the …

A reinforcement learning approach to access management in wireless cellular networks

J Moon, Y Lim - Wireless Communications and Mobile …, 2017 - Wiley Online Library
In smart city applications, huge numbers of devices need to be connected in an autonomous
manner. 3rd Generation Partnership Project (3GPP) specifies that Machine Type …

Joint trajectory design and BS association for cellular-connected UAV: An imitation-augmented deep reinforcement learning approach

YJ Chen, DY Huang - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
This article concerns the problem of the trajectory design and base station (BS) association
for cellular-connected unmanned aerial vehicles (UAVs). To support safety-critical functions …

Dynamic beam hopping for DVB-S2X satellite: A multi-objective deep reinforcement learning approach

Y Zhang, X Hu, R Chen, Z Zhang… - … (IUCC) and Data …, 2019 - ieeexplore.ieee.org
Dynamic Beam Hopping (DBH) is a crucial technology for adapting to the flexibility of
different service configurations in the multi-beam satellite communications market. The …