Quantum Multiagent Actor–Critic Networks for Cooperative Mobile Access in Multi-UAV Systems
C Park, WJ Yun, JP Kim, TK Rodrigues… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
This article proposes a novel algorithm, named quantum multiagent actor–critic networks
(QMACN) for autonomously constructing a robust mobile access system employing multiple …
(QMACN) for autonomously constructing a robust mobile access system employing multiple …
Computational Intelligence Algorithms for UAV Swarm Networking and Collaboration: A Comprehensive Survey and Future Directions
P Cao, L Lei, S Cai, G Shen, X Liu… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Unmanned aerial vehicle (UAV) swarm networking and collaboration have significant
prospects in both civilian and military applications, due to its remarkable properties in …
prospects in both civilian and military applications, due to its remarkable properties in …
Hybrid hierarchical DRL enabled resource allocation for secure transmission in multi-IRS-assisted sensing-enhanced spectrum sharing networks
Secure communications are of paramount importance in spectrum sharing networks due to
the allocation and sharing characteristics of spectrum resources. To further explore the …
the allocation and sharing characteristics of spectrum resources. To further explore the …
A review of research on reinforcement learning algorithms for multi-agents
K Hu, M Li, Z Song, K Xu, Q Xia, N Sun, P Zhou, M Xia - Neurocomputing, 2024 - Elsevier
In recent years, multi-agent reinforcement learning techniques have been widely used and
evolved in the field of artificial intelligence. However, traditional reinforcement learning …
evolved in the field of artificial intelligence. However, traditional reinforcement learning …
Physical layer security enhancement in energy harvesting-based cognitive internet of things: A GAN-powered deep reinforcement learning approach
R Lin, H Qiu, J Wang, Z Zhang, L Wu… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Cognitive radio (CR) is regarded as the key technology of the 6th-Generation (6G) wireless
network. Because 6G CR networks are anticipated to offer worldwide coverage, increase …
network. Because 6G CR networks are anticipated to offer worldwide coverage, increase …
Deep reinforcement learning-based distributed dynamic spectrum access in multi-user multi-channel cognitive radio internet of things networks
X Zhang, Z Chen, Y Zhang, Y Liu… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Integrating cognitive radio into Internet of Things (IoT) is conducive to reducing spectrum
scarcity for large-scale IoT deployment, where a core technology is the design of spectrum …
scarcity for large-scale IoT deployment, where a core technology is the design of spectrum …
A deep-Q learning scheme for secure spectrum allocation and resource management in 6G environment
P Bhattacharya, F Patel, A Alabdulatif… - … on Network and …, 2022 - ieeexplore.ieee.org
In this paper, we propose a dynamic spectrum allocation (DSA) scheme DeepBlocks at the
backdrop of sixth-generation (6G) communication networks that address the challenges of …
backdrop of sixth-generation (6G) communication networks that address the challenges of …
Energy efficient clustering and resource allocation strategy for ultra-dense networks: A machine learning framework
N Sharma, K Kumar - IEEE Transactions on Network and …, 2022 - ieeexplore.ieee.org
The ultra-dense network structure of 5G with dense femto-cells deployment, is identified as a
prospective way out for the problem of growing demand for cellular services. However …
prospective way out for the problem of growing demand for cellular services. However …
Priority-aware access strategy for GF-NOMA system in IIoT: the device-specific allocation approach
To support large-scale connectivity of massive machine-type communication (mMTC)
devices in Industrial Internet of Things (IIoT) scenario, a grant-free (GF) transmission aided …
devices in Industrial Internet of Things (IIoT) scenario, a grant-free (GF) transmission aided …
Online distributed learning-based load-aware heterogeneous vehicular edge computing
L Zhu, Z Zhang, L Liu, L Feng, P Lin… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
Vehicular edge computing (VEC) is an emerging enabler in strengthening driving efficiency
and traffic safety. However, both performance bottlenecks and low-resource efficiency of …
and traffic safety. However, both performance bottlenecks and low-resource efficiency of …