1 citations · 1 across the 7 of their papers we have counts for
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Learning-Based Hybrid Neural Receiver for 6G-V2X Communications
Osama Saleem, Mohammed Alfaqawi, Pierre Merdrignac +2
Neural receiver models are proposed to jointly optimize multiple functionalities of wireless receivers; however, a comprehensive receiver model that replaces the entire physical la…
Differential Transformer-driven 6G Physical Layer for Collaborative Perception Enhancement
Soheyb Ribouh, Osama Saleem, Mohamed Ababsa
The emergence of 6G wireless networks promises to revolutionize vehicular communications by enabling ultra-reliable, low-latency, and high-capacity data exchange. In this context,…
Deep Multimodal Learning for Real-Time DDoS Attacks Detection in Internet of Vehicles
Mohamed Ababsa, Soheyb Ribouh, Abdelhamid Malki +1
The progress and integration of intelligent transport systems (ITS) have therefore been central to creating safer and more efficient transport networks. The Internet of Vehicles (I…
Deep Multi-modal Neural Receiver for 6G Vehicular Communication
Osama Saleem, Mohammed Alfaqawi, Pierre Merdrignac +2
Deep Learning (DL) based neural receiver models are used to jointly optimize PHY of baseline receiver for cellular vehicle to everything (C-V2X) system in next generation (6G) comm…
Large Language Model-Based Semantic Communication System for Image Transmission
Soheyb Ribouh, Osama Saleem
The remarkable success of Large Language Models (LLMs) in understanding and generating various data types, such as images and text, has demonstrated their ability to process and ex…