Efficient resource allocation utilizing Q-learning in multiple UA communications
Y Kawamoto, H Takagi, H Nishiyama… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
In recent years, unmanned aircraft systems (UASs) have garnered significant attention, and
the demand for communication utilizing unmanned aircrafts (UAs) has increased. However …
the demand for communication utilizing unmanned aircrafts (UAs) has increased. However …
Multiagent collaborative learning for uav enabled wireless networks
The unmanned aerial vehicle (UAV) technique provides a potential solution to scalable
wireless edge networks. This paper uses two UAVs, with accelerated motions and fixed …
wireless edge networks. This paper uses two UAVs, with accelerated motions and fixed …
Deep Q-Network based resource allocation for UAV-assisted Ultra-Dense Networks
With the rapid development of the fifth-generation (5G) wireless communications, the
number of users is increasing dramatically and Ultra-Dense Networks (UDN) are becoming …
number of users is increasing dramatically and Ultra-Dense Networks (UDN) are becoming …
A decoupled access scheme with reinforcement learning power control for cellular-enabled UAVs
This article proposes a downlink/uplink decoupled (DUDe) access scheme for cellular-
enabled unmanned aerial vehicle (UAV) communication systems. To minimize interference …
enabled unmanned aerial vehicle (UAV) communication systems. To minimize interference …
DQN-based decentralized multi-agent JSAP resource allocation for UAV swarm communication
J Li, X Dang, S Li - Journal of Systems Engineering and …, 2023 - ieeexplore.ieee.org
It is essential to maximize capacity while satisfying the transmission time delay of unmanned
aerial vehicle (UAV) swarm communication system. In order to address this challenge, a …
aerial vehicle (UAV) swarm communication system. In order to address this challenge, a …
Regret based learning for UAV assisted LTE-U/WiFi public safety networks
Broadband wireless communication is of critical importance during public safety scenarios
as it facilitates situational awareness capabilities for first responders and victims. In this …
as it facilitates situational awareness capabilities for first responders and victims. In this …
Dynamic spectrum interaction of UAV flight formation communication with priority: A deep reinforcement learning approach
The formation flights of multiple unmanned aerial vehicles (UAV) can improve the success
probability of single-machine. Dynamic spectrum interaction solves the problem of the …
probability of single-machine. Dynamic spectrum interaction solves the problem of the …
Optimal Tethered-UAV Deployment in A2G Communication Networks: Multi-Agent Q-Learning Approach
An unmanned aerial vehicle-mounted base station (UAV-BS) is a promising technology for
the forthcoming sixth-generation wireless networks, owing to its flexibility and cost …
the forthcoming sixth-generation wireless networks, owing to its flexibility and cost …
Intelligent dynamic spectrum access using deep reinforcement learning for VANETs
Y Wang, X Li, P Wan, R Shao - IEEE Sensors Journal, 2021 - ieeexplore.ieee.org
In vehicular ad hoc networks (VANETs), vehicles can communicate with other vehicles or
devices through vehicle-to-X communication. However, with the rise of the Internet of Things …
devices through vehicle-to-X communication. However, with the rise of the Internet of Things …
Channel access scheme with alignment reference interval adaptation (ARIA) for frequency reuse in unlicensed band LTE: Fuzzy Q-learning approach
In licensed-assisted access using the LTE (LAA) standard, carrier sensing via the listen-
before-talk (LBT) procedure is a vital feature for fair sharing with the Wi-Fi systems …
before-talk (LBT) procedure is a vital feature for fair sharing with the Wi-Fi systems …