7 papers
Efficient Self-Learning and Model Versioning for AI-native O-RAN Edge
Mounir Bensalem, Fin Gentzen, Tuck-Wai Choong +3
The AI-native vision of 6G requires Radio Access Networks to train, deploy, and continuously refine thousands of machine learning (ML) models that drive real-time radio network opt…
A Secured Intent-Based Networking (sIBN) with Data-Driven Time-Aware Intrusion Detection
Urslla Uchechi Izuazu, Mounir Bensalem, Admela Jukan
While Intent-Based Networking (IBN) promises operational efficiency through autonomous and abstraction-driven network management, a critical unaddressed issue lies in IBN's implici…
On Effectiveness of Graph Neural Network Architectures for Network Digital Twins (NDTs)
Iulisloi Zacarias, Oussama Ben Taarit, Admela Jukan
Future networks, such as 6G, will need to support a vast and diverse range of interconnected devices and applications, each with its own set of requirements. While traditional netw…
A Cross-Layer Analysis of Network Antifragility with RIS-assisted Links under Jamming Attacks
Mounir Bensalem, Thomas Röthig, Admela Jukan
Antifragility is an economics term defined as measure of (monetary) benefits gained from the adverse events and variability of the markets. This paper integrates for the first time…
An Optimization Driven Link SINR Assurance in RIS-assisted Indoor Networks
Cao Vien Phung, Max Franke, Ehsan Tohidi +5
Future smart factories are expected to deploy applications over high-performance indoor wireless channels in the millimeter-wave (mmWave) bands, which on the other hand are suscept…
Optimizing LoRa for Edge Computing with TinyML Pipeline for Channel Hopping
Marla Grunewald, Mounir Bensalem, Admela Jukan
We propose to integrate long-distance LongRange (LoRa) communication solution for sending the data from IoT to the edge computing system, by taking advantage of its unlicensed natu…