Aerospace integrated networks innovation for empowering 6G: A survey and future challenges

D Zhou, M Sheng, J Li, Z Han - IEEE Communications Surveys …, 2023 - ieeexplore.ieee.org
The ever-increasing demand for ubiquitous and differentiated services at anytime and
anywhere emphasizes the necessity of aerospace integrated networks (AINs) which consist …

Reinforcement learning in the sky: A survey on enabling intelligence in ntn-based communications

T Naous, M Itani, M Awad, S Sharafeddine - IEEE Access, 2023 - ieeexplore.ieee.org
Non terrestrial networks (NTN) involving 'in the sky'objects such as low-earth orbit satellites,
high altitude platform systems (HAPs) and Unmanned Aerial Vehicles (UAVs) are expected …

Space-aerial-ground-sea integrated networks: Resource optimization and challenges in 6G

S Sharif, S Zeadally, W Ejaz - Journal of Network and Computer …, 2023 - Elsevier
Abstract Space–air–ground–sea integrated (SAGSI) networks are envisioned to connect
satellite, aerial, ground, and sea networks to provide connectivity everywhere and all the …

A survey on energy optimization techniques in UAV-based cellular networks: from conventional to machine learning approaches

AI Abubakar, I Ahmad, KG Omeke, M Ozturk, C Ozturk… - Drones, 2023 - mdpi.com
Wireless communication networks have been witnessing unprecedented demand due to the
increasing number of connected devices and emerging bandwidth-hungry applications …

Reinforcement learning for energy-efficient trajectory design of UAVs

AH Arani, MM Azari, P Hu, Y Zhu… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
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 …

Joint Rate and Coverage Optimization for the THz/RF Multi-band Communications of Space-air-ground Integrated Network in 6G

X Yuan, F Tang, M Zhao, N Kato - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Space-air-ground integrated networks (SAGIN) incorporating multi-band terahertz (THz) and
radio frequency (RF) communication have gained increasing attention in the 6G era …

HAPS-UAV-enabled heterogeneous networks: A deep reinforcement learning approach

AH Arani, P Hu, Y Zhu - IEEE Open Journal of the …, 2023 - ieeexplore.ieee.org
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 …

[HTML][HTML] Federated Reinforcement Learning for Collaborative Intelligence in UAV-assisted C-V2X Communications

A Gupta, X Fernando - Drones, 2024 - mdpi.com
This paper applies federated reinforcement learning (FRL) in cellular vehicle-to-everything
(C-V2X) communication to enable vehicles to learn communication parameters in …

Fairness-aware link optimization for space-terrestrial integrated networks: A reinforcement learning framework

AH Arani, P Hu, Y Zhu - IEEE Access, 2021 - ieeexplore.ieee.org
The integration of space and air components considering satellites and unmanned aerial
vehicles (UAVs) into terrestrial networks in a space-terrestrial integrated network (STIN) has …

Non-terrestrial networks with UAVs: A projection on flying ad-hoc networks

M Nemati, B Al Homssi, S Krishnan, J Park, SW Loke… - Drones, 2022 - mdpi.com
Non-terrestrial networks (NTNs) have recently attracted elevated levels of interest in large-
scale and ever-growing wireless communication networks through the utilization of flying …