Aerospace integrated networks innovation for empowering 6G: A survey and future challenges
The ever-increasing demand for ubiquitous and differentiated services at anytime and
anywhere emphasizes the necessity of aerospace integrated networks (AINs) which consist …
anywhere emphasizes the necessity of aerospace integrated networks (AINs) which consist …
Machine learning-aided operations and communications of unmanned aerial vehicles: A contemporary survey
Over the past decade, Unmanned Aerial Vehicles (UAVs) have provided pervasive, efficient,
and cost-effective solutions for data collection and communications. Their excellent mobility …
and cost-effective solutions for data collection and communications. Their excellent mobility …
Digital twins in unmanned aerial vehicles for rapid medical resource delivery in epidemics
The purposes are to explore the effect of Digital Twins (DTs) in Unmanned Aerial Vehicles
(UAVs) on providing medical resources quickly and accurately during COVID-19 prevention …
(UAVs) on providing medical resources quickly and accurately during COVID-19 prevention …
Deep-graph-based reinforcement learning for joint cruise control and task offloading for aerial edge internet of things (edgeiot)
This article puts forth an aerial edge Internet of Things (EdgeIoT) system, where an
unmanned aerial vehicle (UAV) is employed as a mobile-edge server to process mission …
unmanned aerial vehicle (UAV) is employed as a mobile-edge server to process mission …
[HTML][HTML] Role of machine learning in resource allocation strategy over vehicular networks: a survey
I Nurcahyani, JW Lee - Sensors, 2021 - mdpi.com
The increasing demand for smart vehicles with many sensing capabilities will escalate data
traffic in vehicular networks. Meanwhile, available network resources are limited. The …
traffic in vehicular networks. Meanwhile, available network resources are limited. The …
Joint communication scheduling and velocity control in multi-UAV-assisted sensor networks: A deep reinforcement learning approach
Recently, Unmanned Aerial Vehicle (UAV) swarm has been increasingly studied to collect
data from ground sensors in remote and hostile areas. A key challenge is the joint design of …
data from ground sensors in remote and hostile areas. A key challenge is the joint design of …
[HTML][HTML] Deep deterministic policy gradient algorithm: A systematic review
Abstract Deep Reinforcement Learning (DRL) has gained significant adoption in diverse
fields and applications, mainly due to its proficiency in resolving complicated decision …
fields and applications, mainly due to its proficiency in resolving complicated decision …
Exploiting a fleet of UAVs for monitoring and data acquisition of a distributed sensor network
This study proposes an efficient data collection strategy exploiting a team of unmanned
aerial vehicles (UAVs) to monitor and collect the data of a large distributed sensor network …
aerial vehicles (UAVs) to monitor and collect the data of a large distributed sensor network …
Deep reinforcement learning-based optimization for end-to-end network slicing with control-and user-plane separation
Control-and user-plane separation (CUPS) and network slicing are two key technologies to
support increasing network traffic and diverse wireless services. However, the benefit of …
support increasing network traffic and diverse wireless services. However, the benefit of …
Deep reinforcement learning for persistent cruise control in UAV-aided data collection
Autonomous UAV cruising is gaining attention due to its flexible deployment in remote
sensing, surveillance, and reconnaissance. A critical challenge in data collection with the …
sensing, surveillance, and reconnaissance. A critical challenge in data collection with the …