Energy-efficient distributed spiking neural network for wireless edge intelligence

Y Liu, Z Qin, GY Li - IEEE Transactions on Wireless …, 2024 - ieeexplore.ieee.org
The spiking neural network (SNN) is distinguished by its ultra-low power consumption,
making it attractive for resource-limited edge intelligence. This paper investigates an energy …

Enhancing cybersecurity in the internet of things environment using bald eagle search optimization with hybrid deep learning

LA Maghrabi, S Shabanah, T Althaqafi… - IEEE …, 2024 - ieeexplore.ieee.org
Nowadays, the Internet of Things (IoT) has become a rapid development; it can be employed
by cyber threats in IoT devices. A correct system to recognize malicious attacks at IoT …

Artificial intelligence techniques for next-generation massive satellite networks

B Al Homssi, K Dakic, K Wang, T Alpcan… - IEEE …, 2023 - ieeexplore.ieee.org
Space communications, particularly massive satellite networks, re-emerged as an appealing
candidate for next generation networks due to major advances in space launching …

Artificial intelligence techniques for next-generation mega satellite networks

BA Homssi, K Dakic, K Wang, T Alpcan, B Allen… - arxiv preprint arxiv …, 2022 - arxiv.org
Space communications, particularly massive satellite networks, re-emerged as an appealing
candidate for next generation networks due to major advances in space launching …

Spiking Neural Networks for Detecting Satellite Internet of Things Signals

K Dakic, B Al Homssi, S Walia… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With the rapid growth of Internet of Things (IoT) networks, ubiquitous coverage is becoming
increasingly necessary. Low earth orbit (LEO) satellite constellations for the IoT have been …

Deep learning in wireless communications for physical layer

J Zhao, C Liu, J Liao, D Wang - Physical Communication, 2024 - Elsevier
Current wireless communication faces challenges of spectrum congestion, interference, and
accommodating Internet of Things and 5G demands. Artificial intelligence (AI) has recently …

[HTML][HTML] Enhancing IoT Security Using GA-HDLAD: A Hybrid Deep Learning Approach for Anomaly Detection

I Mutambik - Applied Sciences, 2024 - mdpi.com
The adoption and use of the Internet of Things (IoT) have increased rapidly over recent
years, and cyber threats in IoT devices have also become more common. Thus, the …

Intelligent index classification method based on machine learning for detection of reference signal in 5G networks

S Kang, T Lee, J Kim, J Kim, O Jo - IEEE Access, 2023 - ieeexplore.ieee.org
In order to maintain stable communication in 5G wireless networks, the link between a 5G
base station and user equipment (UE) should be constantly monitored and adapted to the …

Analysis and Prediction of Mobile Industrial Internet of Things (IIoT) Communications Based on FL-GLP-Net

L Xu, S Cao, X Li, TA Gulliver - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
The number of mobile users and applications is rising quickly due to the deployment of fifth-
generation (5G) communication technology. The prevalence of smart devices and Internet of …

Spiking-unet: Spiking neural networks for spectrum occupancy monitoring

K Dakic, B Al Homssi… - 2024 IEEE Wireless …, 2024 - ieeexplore.ieee.org
With the exponential growth of the Internet of Things (IoT) landscape and the resulting
spectrum congestion, innovative techniques for spectrum monitoring are crucial. This paper …