Distributed artificial intelligence enabled aerial-ground networks: Architecture, technologies and challenges
Artificial intelligence (AI) provides a promising and novel direction to design future time-
varying wireless networks by leading to significantly superior performances compared to …
varying wireless networks by leading to significantly superior performances compared to …
A review on AI-driven aerial access networks: Challenges and open research issues
Aerial access networks (AANs) consisting of low altitude platforms (LAPs) and high altitude
platforms (HAPs) have been considered as emerging wireless networking technologies to …
platforms (HAPs) have been considered as emerging wireless networking technologies to …
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 …
Security-aware resource sharing in software defined air-ground integrated networks: A game approach
To accommodate the surge of data traffic in unmanned aerial vehicle (UAV) applications,
software defined air-ground integrated networks (SD-AGNs) hold great potentials for efficient …
software defined air-ground integrated networks (SD-AGNs) hold great potentials for efficient …
AI-enabled space-air-ground integrated networks: Management and optimization
AI-enabled Beyond 5G (B5G) and 6G technologies are promising candidates to support the
future generation Space-Air-Ground Integrated Networks (SAGINs). The highly dynamic …
future generation Space-Air-Ground Integrated Networks (SAGINs). The highly dynamic …
Exploiting UAV for air–ground integrated federated learning: A joint UAV location and resource optimization approach
Y Jing, Y Qu, C Dong, W Ren, Y Shen… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Recently, many exciting usage scenarios and groundbreaking technologies for sixth
generation (6G) networks have drawn more and more attention. The revolution of 6G mainly …
generation (6G) networks have drawn more and more attention. The revolution of 6G mainly …
Nexus of Deep Reinforcement Learning and Leader–Follower Approach for AIoT Enabled Aerial Networks
The Industrial Internet of Things (IIoT) is a new industrial 4.0 paradigm that combines IoT,
robotics, cyber-physical systems, and other future industrial advancements. Unmanned …
robotics, cyber-physical systems, and other future industrial advancements. Unmanned …
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 …
Air-Ground Collaborative Edge Intelligence for Future Generation Networks
The air-ground integrated mobile edge computing (MEC) is expected to fulfill the ever-
growing resource demands of artificial intelligence (AI)-enabled applications in sixth …
growing resource demands of artificial intelligence (AI)-enabled applications in sixth …
Cooperative Multi-Type Multi-Agent Deep Reinforcement Learning for Resource Management in Space-Air-Ground Integrated Networks
The Space-Air-Ground Integrated Network (SAGIN), integrating heterogeneous devices
including low earth orbit (LEO) satellites, unmanned aerial vehicles (UAVs), and ground …
including low earth orbit (LEO) satellites, unmanned aerial vehicles (UAVs), and ground …