Path planning for cellular-connected UAV: A DRL solution with quantum-inspired experience replay
In cellular-connected unmanned aerial vehicle (UAV) network, a minimization problem on
the weighted sum of time cost and expected outage duration is considered. Taking …
the weighted sum of time cost and expected outage duration is considered. Taking …
Cellular-connected UAV trajectory design with connectivity constraint: A deep reinforcement learning approach
Cellular-connected unmanned aerial vehicle (UAV) communication has attracted
increasingly attention recently. We consider a cellular-connected UAV carried with limited on …
increasingly attention recently. We consider a cellular-connected UAV carried with limited on …
Simultaneous navigation and radio mapping for cellular-connected UAV with deep reinforcement learning
Cellular-connected unmanned aerial vehicle (UAV) is a promising technology to unlock the
full potential of UAVs in the future by reusing the cellular base stations (BSs) to enable their …
full potential of UAVs in the future by reusing the cellular base stations (BSs) to enable their …
Path design for cellular-connected UAV with reinforcement learning
This paper studies the path design problem for cellular-connected unmanned aerial vehicle
(UAV), which aims to minimize its mission completion time while maintaining good …
(UAV), which aims to minimize its mission completion time while maintaining good …
Deep reinforcement learning for interference-aware path planning of cellular-connected UAVs
In this paper, an interference-aware path planning scheme for a network of cellular-
connected unmanned aerial vehicles (UAVs) is proposed. In particular, each UAV acts as a …
connected unmanned aerial vehicles (UAVs) is proposed. In particular, each UAV acts as a …
Deep reinforcement learning for UAV trajectory design considering mobile ground users
W Lee, Y Jeon, T Kim, YI Kim - Sensors, 2021 - mdpi.com
A network composed of unmanned aerial vehicles (UAVs), serving as base stations (UAV-
BS network), is emerging as a promising component in next-generation communication …
BS network), is emerging as a promising component in next-generation communication …
Reinforcement learning for decentralized trajectory design in cellular UAV networks with sense-and-send protocol
Recently, the unmanned aerial vehicles (UAVs) have been widely used in real-time sensing
applications over cellular networks. The performance of a UAV is determined by both its …
applications over cellular networks. The performance of a UAV is determined by both its …
Deep reinforcement learning based resource allocation and trajectory planning in integrated sensing and communications UAV network
Y Qin, Z Zhang, X Li, W Huangfu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In this paper, multi-UAVs serve as mobile aerial ISAC platforms to sense and communicate
with on-ground target users. To optimize the communication and sensing performance, we …
with on-ground target users. To optimize the communication and sensing performance, we …
Autonomous UAV path planning using modified PSO for UAV-assisted wireless networks
Recently, unmanned aerial vehicles (UAVs) have attained considerable attention for
providing reliable and cost-effective communication due to the flexibility of deployment and …
providing reliable and cost-effective communication due to the flexibility of deployment and …
Learning-based UAV trajectory optimization with collision avoidance and connectivity constraints
Unmanned aerial vehicles (UAVs) are expected to be an integral part of wireless networks,
and determining collision-free trajectories for multiple UAVs while satisfying requirements of …
and determining collision-free trajectories for multiple UAVs while satisfying requirements of …