50 citations · 142 across the 22 of their papers we have counts for
8 papers · 1 filter
Comprehensive RF Dataset Collection and Release: A Deep Learning-Based Device Fingerprinting Use Case
Abdurrahman Elmaghbub, Bechir Hamdaoui
Deep learning-based RF fingerprinting has recently been recognized as a potential solution for enabling newly emerging wireless network applications, such as spectrum access policy…
Leveraging Multiple Transmissions and Receptions for Channel-Agnostic Deep Learning-Based Network Device Classification
Nora Basha, Bechir Hamdaoui
The accurate identification of wireless devices is critical for enabling automated network access monitoring and authenticated data communication in large-scale networks; e.g., IoT…
Deep Neural Network Feature Designs for RF Data-Driven Wireless Device Classification
Bechir Hamdaoui, Abdurrahman Elmaghbub, Seifeddine Mejri
Most prior works on deep learning-based wireless device classification using radio frequency (RF) data apply off-the-shelf deep neural network (DNN) models, which were matured main…
Leveraging Hardware-Impaired Out-of-Band Information Through Deep Neural Networks for Robust Wireless Device Classification
Abdurrahman Elmaghbub, Bechir Hamdaoui
Wireless device classification techniques play a key role in promoting emerging wireless applications such as allowing spectrum regulatory agencies to enforce their access policies…
Mixed RF/FSO Relaying Systems with Hardware Impairments
Elyes Balti, Mohsen Guizani, Bechir Hamdaoui +1
In this work, we provide a detailed analysis of a dual-hop fixed gain (FG) amplify-and-forward relaying system, consisting of a hybrid radio frequency (RF) and free-space optical (…
Aggregate Hardware Impairments Over Mixed RF/FSO Relaying Systems With Outdated CSI
Elyes Balti, Mohsen Guizani, Bechir Hamdaoui +1
In this paper, we propose a dual-hop RF (Radio-Frequency)/FSO (Free-Space Optical) system with multiple relays employing the Decode-and-Forward (DF) and Amplify-and-Forward (AF) wi…