Deployment of Unmanned Aerial Vehicles in Next-Generation Wireless Communication Network using Multi-Agent Reinforcement Learning
To address the challenges posed by a large number of disaster-waiver-affected users and
the complexities of scaling centralized algorithms for rapidly restoring emergency …
the complexities of scaling centralized algorithms for rapidly restoring emergency …
Resource allocation in UAV-assisted networks: A clustering-aided reinforcement learning approach
S Zhou, Y Cheng, X Lei, Q Peng… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
As an aerial base station, unmanned aerial vehicle (UAV) has been considered as a
promising technology to assist future wireless communications due to its flexible, swift and …
promising technology to assist future wireless communications due to its flexible, swift and …
Multi-agent reinforcement learning for cooperative trajectory design of UAV-BS fleets in terrestrial/non-terrestrial integrated networks
Aerial base stations (ABSs) have been envisioned as a promising technology toward
ubiquitous coverage and seamless high-rate connectivity in sixth-generation (6G) wireless …
ubiquitous coverage and seamless high-rate connectivity in sixth-generation (6G) wireless …
QoE-driven adaptive deployment strategy of multi-UAV networks based on hybrid deep reinforcement learning
Y Zhou, X Ma, S Hu, D Zhou… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) serve as aerial base stations to provide controlled
wireless connections for ground users. Due to their constraints on both mobility and energy …
wireless connections for ground users. Due to their constraints on both mobility and energy …
Multi-agent learning approach for uavs enabled wireless networks
The unmanned aerial vehicle (UAV) technology provides a potential solution to scalable
wireless edge networks. This paper uses two UAVs, with accelerated motions and fixed …
wireless edge networks. This paper uses two UAVs, with accelerated motions and fixed …
Multiagent Q-Learning-Based Multi-UAV Wireless Networks for Maximizing Energy Efficiency: Deployment and Power Control Strategy Design
In air-to-ground communications, the network lifetime depends on the operation time of
unmanned aerial vehicle-base stations (UAV-BSs) owing to the restricted battery capacity …
unmanned aerial vehicle-base stations (UAV-BSs) owing to the restricted battery capacity …
UAV-assisted 5G/6G networks: Joint scheduling and resource allocation based on asynchronous reinforcement learning
Unmanned aerial vehicles (UAVs) can be used as flying base stations (BSs) for providing
wireless communications and coverage enhancement in fifth/sixth-generation (5G/6G) …
wireless communications and coverage enhancement in fifth/sixth-generation (5G/6G) …
Machine Learning Techniques for UAV-Assisted Networks
A Shahbazi - 2022 - theses.hal.science
The main focus of this thesis is on modeling, performance evaluation and system-level
optimization of next-generation cellular networks empowered by Unmanned Aerial Vehicles …
optimization of next-generation cellular networks empowered by Unmanned Aerial Vehicles …
HAPS-UAV-enabled heterogeneous networks: A deep reinforcement learning approach
The integrated use of non-terrestrial network (NTN) entities such as the high-altitude
platform station (HAPS) and low-altitude platform station (LAPS) has become essential …
platform station (HAPS) and low-altitude platform station (LAPS) has become essential …
Density-Aware Reinforcement Learning to Optimise Energy Efficiency in UAV-Assisted Networks
Unmanned aerial vehicles (UAVs) serving as aerial base stations can be deployed to
provide wireless connectivity to mobile users, such as vehicles. However, the density of …
provide wireless connectivity to mobile users, such as vehicles. However, the density of …