Deep reinforcement learning based resource allocation and trajectory planning in integrated sensing and communications UAV network
Y Qin, Z Zhang, X Li, W Huangfu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In this paper, multi-UAVs serve as mobile aerial ISAC platforms to sense and communicate
with on-ground target users. To optimize the communication and sensing performance, we …
with on-ground target users. To optimize the communication and sensing performance, we …
Computing assistance from the sky: Decentralized computation efficiency optimization for air-ground integrated MEC networks
This letter proposes a multi-agent deep reinforcement learning (MADRL) framework for
resource allocation in air-ground integrated multi-access edge computing (MEC) networks …
resource allocation in air-ground integrated multi-access edge computing (MEC) networks …
Spectrum-sharing UAV-assisted mission-critical communication: Learning-aided real-time optimisation
MHT Nguyen, E Garcia-Palacios, T Do-Duy… - IEEE …, 2021 - ieeexplore.ieee.org
We propose an unmanned aerial vehicle (UAV) communications scheme with spectrum-
sharing mechanism to provide mission-critical services such as disaster recovery and public …
sharing mechanism to provide mission-critical services such as disaster recovery and public …
UAV-Enabled Integrated Sensing and Communication in Maritime Emergency Networks
With line-of-sight mode deployment and fast response, unmanned aerial vehicle (UAV),
equipped with the cutting-edge integrated sensing and communication (ISAC) technique, is …
equipped with the cutting-edge integrated sensing and communication (ISAC) technique, is …
Energy sustainability in dense radio access networks via high altitude platform stations
M Salamatmoghadasi, A Mehrabian… - IEEE Networking …, 2023 - ieeexplore.ieee.org
The growing demand for radio access networks (RANs) driven by advanced wireless
technology and the ever-increasing mobile traffic, faces significant energy consumption …
technology and the ever-increasing mobile traffic, faces significant energy consumption …
Reinforcement learning for energy-efficient trajectory design of UAVs
Integrating unmanned aerial vehicles (UAVs) as aerial base stations (BSs) into terrestrial
cellular networks has emerged as an effective solution to provide coverage and complement …
cellular networks has emerged as an effective solution to provide coverage and complement …
Multi-agent deep reinforcement learning for optimising energy efficiency of fixed-wing UAV cellular access points
Unmanned Aerial Vehicles (UAVs) promise to become an intrinsic part of next generation
communications, as they can be deployed to provide wireless connectivity to ground users …
communications, as they can be deployed to provide wireless connectivity to ground users …
Federated reinforcement learning based AANs with LEO satellites and UAVs
Supported by the advances in rocket technology, companies like SpaceX and Amazon
competitively have entered the satellite Internet business. These companies said that they …
competitively have entered the satellite Internet business. These companies said that they …
Reinforcement Learning for Energy-Efficient User Association in UAV-Assisted Cellular Networks
In unmanned aerial vehicle (UAV)-assisted communications, there are two significant
challenges that need to be addressed—optimized UAV placement and energy-efficient user …
challenges that need to be addressed—optimized UAV placement and energy-efficient user …
SAC-based UAV mobile edge computing for energy minimization and secure data transmission
X Zhao, T Zhao, F Wang, Y Wu, M Li - Ad Hoc Networks, 2024 - Elsevier
In recent years, the use of UAVs to carry mobile edge computing servers has become an
emerging solution to the problem of collaborative ground-to-air communication. However …
emerging solution to the problem of collaborative ground-to-air communication. However …