3 citations · 7 across the 12 of their papers we have counts for
6 papers · 1 filter
NetOrchLLM: Mastering Wireless Network Orchestration with Large Language Models
Asmaa Abdallah, Abdullatif Albaseer, Abdulkadir Celik +2
The transition to 6G networks promises unprecedented advancements in wireless communication, with increased data rates, ultra-low latency, and enhanced capacity. However, the compl…
Optimized Federated Multitask Learning in Mobile Edge Networks: A Hybrid Client Selection and Model Aggregation Approach
Moqbel Hamood, Abdullatif Albaseer, Mohamed Abdallah +2
We propose clustered federated multitask learning to address statistical challenges in non-independent and identically distributed data across clients. Our approach tackles complex…
Energy-Aware Service Offloading for Semantic Communications in Wireless Networks
Hassan Saadat, Abdullatif Albaseer, Mohamed Abdallah +2
Today, wireless networks are becoming responsible for serving intelligent applications, such as extended reality and metaverse, holographic telepresence, autonomous transportation,…
Empowering HWNs with Efficient Data Labeling: A Clustered Federated Semi-Supervised Learning Approach
Moqbel Hamood, Abdullatif Albaseer, Mohamed Abdallah +1
Clustered Federated Multitask Learning (CFL) has gained considerable attention as an effective strategy for overcoming statistical challenges, particularly when dealing with non in…
Tailoring Semantic Communication at Network Edge: A Novel Approach Using Dynamic Knowledge Distillation
Abdullatif Albaseer, Mohamed Abdallah
Semantic Communication (SemCom) systems, empowered by deep learning (DL), represent a paradigm shift in data transmission. These systems prioritize the significance of content over…
Fair Selection of Edge Nodes to Participate in Clustered Federated Multitask Learning
Abdullatif Albaseer, Mohamed Abdallah, Ala Al-Fuqaha +3
Clustered federated Multitask learning is introduced as an efficient technique when data is unbalanced and distributed amongst clients in a non-independent and identically distribu…