Multi-UAV assisted network coverage optimization for rescue operations using reinforcement learning
Mobile communication networks could make a significant difference in rescuing affected
people in post-disaster scenarios. However, the existing communication infrastructures tend …
people in post-disaster scenarios. However, the existing communication infrastructures tend …
Energy-efficient multi-uavs cooperative trajectory optimization for communication coverage: An madrl approach
T Ao, K Zhang, H Shi, Z Jin, Y Zhou, F Liu - Remote Sensing, 2023 - mdpi.com
Unmanned Aerial Vehicles (UAVs) can be deployed as aerial wireless base stations which
dynamically cover the wireless communication networks for Ground Users (GUs). The most …
dynamically cover the wireless communication networks for Ground Users (GUs). The most …
Deep reinforcement learning for UAV-assisted emergency response
In the aftermath of a disaster, the ability to reliably communicate and coordinate emergency
response could make a meaningful difference in the number of lives saved or lost. However …
response could make a meaningful difference in the number of lives saved or lost. However …
[HTML][HTML] Communication-enabled deep reinforcement learning to optimise energy-efficiency in UAV-assisted networks
Unmanned aerial vehicles (UAVs) are increasingly deployed to provide wireless
connectivity to static and mobile ground users in situations of increased network demand or …
connectivity to static and mobile ground users in situations of increased network demand or …
Energy-efficient UAV control for effective and fair communication coverage: A deep reinforcement learning approach
Unmanned aerial vehicles (UAVs) can be used to serve as aerial base stations to enhance
both the coverage and performance of communication networks in various scenarios, such …
both the coverage and performance of communication networks in various scenarios, such …
UAV base station trajectory optimization based on reinforcement learning in post-disaster search and rescue operations
Because of disaster, terrestrial base stations (TBS) would be partly crashed. Some user
equipments (UE) would be unserved. Deploying unmanned aerial vehicles (UAV) as aerial …
equipments (UE) would be unserved. Deploying unmanned aerial vehicles (UAV) as aerial …
5G Network on Wings: A Deep Reinforcement Learning Approach to the UAV-based Integrated Access and Backhaul
Fast and reliable wireless communication has become a critical demand in human life. In the
case of mission-critical (MC) scenarios, for instance, when natural disasters strike, providing …
case of mission-critical (MC) scenarios, for instance, when natural disasters strike, providing …
Dense Multi-Agent Reinforcement Learning Aided Multi-UAV Information Coverage for Vehicular Networks
With the rapid development of wireless communication networks, UAVs serving as base
stations are increasingly being applied in various scenarios which not only include edge …
stations are increasingly being applied in various scenarios which not only include edge …
On uav serving node deployment for temporary coverage in forest environment: A hierarchical deep reinforcement learning approach
Unmanned aerial vehicles (UAVs) can be effectively used as serving stations in emergency
communications because of their free movements, strong flexibility, and dynamic coverage …
communications because of their free movements, strong flexibility, and dynamic coverage …
Classical versus reinforcement learning algorithms for unmanned aerial vehicle network communication and coverage path planning: A systematic literature review
A Mannan, MS Obaidat, K Mahmood… - International Journal …, 2023 - Wiley Online Library
The unmanned aerial vehicle network communication includes all points of interest during
the coverage path planning. Coverage path planning in such networks is crucial for many …
the coverage path planning. Coverage path planning in such networks is crucial for many …