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Toward autonomous multi-UAV wireless network: A survey of reinforcement learning-based approaches
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 …
research interest in recent years and are gradually being utilized in various aspects of our …
Unmanned aerial vehicle communications for civil applications: A review
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 …
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
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) …
communications (ISAC) system in the multiuser multiple-input multiple-output (MIMO) …
Explainable AI for 6G use cases: Technical aspects and research challenges
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 …
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
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 …
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
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 …
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
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 …
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
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 …
has attracted wide attention as one of the cornerstones of modern service architectures. An …
Noma for star-ris assisted uav networks
This paper proposes a novel simultaneously transmitting and reflecting reconfigurable
intelligent surface (STAR-RIS) assisted unmanned aerial vehicle (UAV) non-orthogonal …
intelligent surface (STAR-RIS) assisted unmanned aerial vehicle (UAV) non-orthogonal …
A survey of object goal navigation
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 …
environment, which is an ability often required in the accomplishment of complex tasks …