Dynamic channel selection and transmission scheduling for cognitive radio networks

X Zhu, Y Huang, Q Wu, F Zhou, X Ge… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
Cognitive radio networks (CRNs) are expected to be promising techniques for improving the
spectrum efficiency of wireless network utility in the squeezed sub-6-GHz frequency bands …

Distributed resource allocation for URLLC in IIoT scenarios: A multi-armed bandit approach

F Pase, M Giordani, G Cuozzo… - 2022 IEEE …, 2022 - ieeexplore.ieee.org
This paper addresses the problem of enabling inter-machine Ultra-Reliable Low-Latency
Communication (URLLC) in future 6G Industrial Internet of Things (IIoT) networks. As far as …

Control of electromagnetic radiation on coexisting smart radio environment

MM Şahin, H Arslan, KC Chen - IEEE Open Journal of the …, 2022 - ieeexplore.ieee.org
Efficient spectrum utilization is always the fundamental challenge of mobile communication
technology toward 6G. Instead of conventional spectral efficiency in bps/Hz, geographical …

Fog-GMFA-DRL: Enhanced deep reinforcement learning with hybrid grey wolf and modified moth flame optimization to enhance the load balancing in the fog-IoT …

S Gupta, N Singh - Advances in Engineering Software, 2022 - Elsevier
Abstract Internet of Things (IoT) can facilitate a plethora of data transactions among various
servers. In the IoT, fog servers are utilized to achieve effective data transactions from …

Effective throughput maximization of NOMA with practical modulations

Y Wang, J Wang, VWS Wong… - IEEE Journal on Selected …, 2022 - ieeexplore.ieee.org
Non-orthogonal multiple access (NOMA) has been considered as a promising technology
for future wireless communications. In most of the existing NOMA schemes, the ideal …

AI-based radio resource allocation in support of the massive heterogeneity of 6G networks

A Alwarafy, A Albaseer, BS Ciftler… - 2021 IEEE 4th 5G …, 2021 - ieeexplore.ieee.org
There is a consensus in industry and academia that 6G wireless networks will incorporate
massive heterogeneous radio access technologies (RATs) in order to cater to the high …

An AI-Assisted Smart Healthcare System Using 5G Communication

B Pradhan, S Das, DS Roy, S Routray… - IEEE …, 2023 - ieeexplore.ieee.org
Technology's fast growth has profoundly impacted myriad areas, including healthcare.
Implementing 5G networks offering high-speed and low-latency communication capabilities …

Enhanced hybrid hierarchical federated edge learning over heterogeneous networks

Q Chen, Z You, D Wen, Z Zhang - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In this work, a Hybrid Hierarchical Federated Edge Learning (HHFEL) architecture that
consists of a device layer, an edge layer, and a cloud layer over heterogeneous networks, is …

Implementation of deep-learning-based csi feedback reporting on 5g nr-compliant link-level simulator

DG Riviello, R Tuninato, E Zimaglia, R Fantini… - Sensors, 2023 - mdpi.com
Advances in machine learning have widened the range of its applications in many fields. In
particular, deep learning has attracted much interest for its ability to provide solutions where …

How can applications of blockchain and artificial intelligence improve performance of Internet of Things?–A survey

P Bothra, R Karmakar, S Bhattacharya, S De - Computer Networks, 2023 - Elsevier
In the era of the Internet of Things (IoT), massive computing devices surrounding us operate
and interact with each other to provide several significant services in industries, medical as …