Opportunistic non-contiguous OFDMA scheduling framework for future B5G/6G cellular networks

HB Salameh, H Al-Obiedollah, R Mahasees… - … Modelling Practice and …, 2022 - Elsevier
In this paper, we consider the problem of resource allocation within Beyond 5G (B5G) and
the envisioned 6G wireless networks with Cognitive Radio (CR) capability. CR technology …

Key Technologies and Applications of UAVs in Underground Space: A Review

B He, X Ji, G Li, B Cheng - IEEE Transactions on Cognitive …, 2024 - ieeexplore.ieee.org
Robots, particularly unmanned aerial vehicles (UAVs), offer significant advantages in
challenging environments. Their application in searching and exploring underground areas …

[HTML][HTML] A dynamic algorithm for interference management in D2D-enabled heterogeneous cellular networks: Modeling and analysis

M Kamruzzaman, NI Sarkar, J Gutierrez - Sensors, 2022 - mdpi.com
To supporting a wider and diverse range of applications, device-to-device (D2D)
communication is a key enabler in heterogeneous cellular networks (HetCNets). It plays an …

[HTML][HTML] A Scalable Video Multicast Scheme Based on User Demand Perception and D2D Communication

R Ouyang, X Xiong, M Fu, J Wang, S Chen, O Alfarraj - Sensors, 2023 - mdpi.com
With the widespread application of 5G technology, there has been a significant surge in
wireless video service demand and video traffic due to the proliferation of smart terminal …

Deep reinforcement learning‐based resource allocation in multi‐access edge computing

M Khani, MM Sadr, S Jamali - Concurrency and Computation …, 2023 - Wiley Online Library
Network architects and engineers face challenges in meeting the increasing complexity and
low‐latency requirements of various services. To tackle these challenges, multi‐access …

[HTML][HTML] Deep reinforcement learning based resource allocation for D2D communications underlay cellular networks

S Yu, JW Lee - Sensors, 2022 - mdpi.com
In this paper, a resource allocation (RA) scheme based on deep reinforcement learning
(DRL) is designed for device-to-device (D2D) communications underlay cellular networks …

[HTML][HTML] Multi-agent deep reinforcement learning based resource management in heterogeneous V2X networks

J Zhao, F Hu, J Li, Y Nie - Digital Communications and Networks, 2023 - Elsevier
Abstract In Heterogeneous Vehicle-to-Everything Networks (HVNs), multiple users such as
vehicles and handheld devices and infrastructure can communicate with each other to …

Adversarial Domain Generalization Defense via Task-Relevant Feature Alignment in Cyber-Physical Systems

S Zhang, J Liu, Z Bao, Y Yang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Automatic modulation classification (AMC) is a key technology in cyber-physical systems
(CPSs), which enables the monitoring and identification of communication signals …

AI-based resource allocation techniques in D2D communication: Open issues and future directions

T Rathod, S Tanwar - Physical Communication, 2024 - Elsevier
Abstract The fifth-generation (5G) mobile network enhances network connectivity between
many mobile devices by utilizing higher bandwidth with lower communication delay. This …

[HTML][HTML] Load based dynamic channel allocation model to enhance the performance of device-to-device communication in WPAN

J Logeshwaran, RN Shanmugasundaram, J Lloret - Wireless Networks, 2024 - Springer
The modern communication network has advanced to such an extent that it is now possible
for devices within a wireless personal area network (WPAN) to communicate among …