Intelligent spectrum sensing and access with partial observation based on hierarchical multi-agent deep reinforcement learning

X Li, Y Zhang, H Ding, Y Fang - IEEE Transactions on Wireless …, 2023 - ieeexplore.ieee.org
Dynamic spectrum access (DSA) has been regarded as a viable solution to the spectrum
shortage problem. To find idle spectrum, partial spectrum sensing could be employed by …

Deep reinforcement learning for resource allocation with network slicing in cognitive radio network

S Yuan, Y Zhang, W Qie, T Ma, S Li - Computer Science and …, 2021 - doiserbia.nb.rs
With the development of wireless communication technology, the requirement for data rate is
growing rapidly. Mobile communication system faces the problem of shortage of spectrum …

Historical spectrum sensing data mining for cognitive radio enabled vehicular ad-hoc networks

XL Huang, J Wu, W Li, Z Zhang… - IEEE transactions on …, 2015 - ieeexplore.ieee.org
In vehicular ad-hoc network (VANET), the reliability of communication is associated with
driving safety. However, research shows that the safety-message transmission in VANET …

Multi-Agent Reinforcement Learning Resources Allocation Method Using Dueling Double Deep Q-Network in Vehicular Networks

Y Ji, Y Wang, H Zhao, G Gui, H Gacanin… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
The communications between vehicle-to-vehicle (V2V) with high frequency, group sending,
group receiving and periodic lead to serious collision of wireless resources and limited …

Performance analysis of cooperative spectrum sensing in cognitive vehicular networks with dense traffic

S Zhu, C Guo, C Feng, X Liu - 2016 IEEE 83rd Vehicular …, 2016 - ieeexplore.ieee.org
Cognitive Radio (CR) is a promising technology to solve the spectrum scarcity. Spectrum
sensing becomes more challenging in Cognitive Vehicular Networks (CVNs) due to …

Cognitive carrier resource optimization for internet-of-vehicles in 5g-enhanced smart cities

F Li, KY Lam, Z Ni, D Niyato, X Liu, L Wang - IEEE Network, 2021 - ieeexplore.ieee.org
Internet-of-Vehicles (IoV), an important part of Intelligent Transportation Systems, is one of
the most strategic applications in smart cities initiatives. The mMTC and URLLC functions of …

[HTML][HTML] Deep Reinforcement Learning-Based Resource Allocation for Cellular Vehicular Network Mode 3 with Underlay Approach

J Fu, X Qin, Y Huang, L Tang, Y Liu - Sensors, 2022 - mdpi.com
Vehicle-to-vehicle (V2V) communication has attracted increasing attention since it can
improve road safety and traffic efficiency. In the underlay approach of mode 3, the V2V links …

Improving vehicular safety message delivery through the implementation of a cognitive vehicular network

AJ Ghandour, K Fawaz, H Artail, M Di Felice, L Bononi - Ad hoc networks, 2013 - Elsevier
Abstract The Wireless Access in Vehicular Environments (WAVE) protocol stack has been
recently defined to enable vehicular communication on the Dedicated Short Range …

Performance analysis of a cognitive radio contention-aware channel selection algorithm

A Mesodiakaki, F Adelantado, L Alonso… - IEEE Transactions …, 2014 - ieeexplore.ieee.org
In cognitive radio (CR) networks, due to the ever increasing traffic demands and the limited
spectrum resources, it is very likely for several secondary networks (SNs) to coexist and …

Spectrum-and Energy-Efficiency Analysis Under Sensing Delay Constraint for Cognitive Unmanned Aerial Vehicle Networks

J Zhang, J Wu, Z Chen, Z Chen, J Gan… - KSII Transactions on …, 2022 - koreascience.kr
In order to meet the rapid development of the unmanned aerial vehicle (UAV)
communication needs, cooperative spectrum sensing (CSS) helps to identify unused …