Toward autonomous multi-UAV wireless network: A survey of reinforcement learning-based approaches

Y Bai, H Zhao, X Zhang, Z Chang… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
Unmanned aerial vehicle (UAV)-based wireless networks have received increasing
research interest in recent years and are gradually being utilized in various aspects of our …

Unmanned aerial vehicle communications for civil applications: A review

M Ghamari, P Rangel, M Mehrubeoglu… - IEEE …, 2022 - ieeexplore.ieee.org
The use of drones, formally known as unmanned aerial vehicles (UAVs), has significantly
increased across a variety of applications over the past few years. This is due to the rapid …

Fluid antenna system liberating multiuser MIMO for ISAC via deep reinforcement learning

C Wang, G Li, H Zhang, KK Wong, Z Li… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
The aim of this paper is to enhance the performance of an integrated sensing and
communications (ISAC) system in the multiuser multiple-input multiple-output (MIMO) …

Explainable AI for 6G use cases: Technical aspects and research challenges

S Wang, MA Qureshi… - IEEE Open Journal …, 2024 - ieeexplore.ieee.org
Around 2020, 5G began its commercialization journey, and discussions about the next-
generation networks (such as 6G) emerged. Researchers predict that 6G networks will have …

Applications of explainable AI for 6G: Technical aspects, use cases, and research challenges

S Wang, MA Qureshi, L Miralles-Pechuan… - arxiv preprint arxiv …, 2021 - arxiv.org
When 5G began its commercialisation journey around 2020, the discussion on the vision of
6G also surfaced. Researchers expect 6G to have higher bandwidth, coverage, reliability …

Bayesian optimization enhanced deep reinforcement learning for trajectory planning and network formation in multi-UAV networks

S Gong, M Wang, B Gu, W Zhang… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
In this paper, we employ multiple UAVs coordinated by a base station (BS) to help the
ground users (GUs) to offload their sensing data. Different UAVs can adapt their trajectories …

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 …

A survey on computation offloading in edge systems: From the perspective of deep reinforcement learning approaches

P Peng, W Lin, W Wu, H Zhang, S Peng, Q Wu… - Computer Science …, 2024 - Elsevier
Driven by the demand of time-sensitive and data-intensive applications, edge computing
has attracted wide attention as one of the cornerstones of modern service architectures. An …

Noma for star-ris assisted uav networks

J Lei, T Zhang, X Mu, Y Liu - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
This paper proposes a novel simultaneously transmitting and reflecting reconfigurable
intelligent surface (STAR-RIS) assisted unmanned aerial vehicle (UAV) non-orthogonal …

A survey of object goal navigation

J Sun, J Wu, Z Ji, YK Lai - IEEE Transactions on Automation …, 2024 - ieeexplore.ieee.org
Object Goal Navigation (ObjectNav) refers to an agent navigating to an object in an unseen
environment, which is an ability often required in the accomplishment of complex tasks …