122 citations · 148 across the 22 of their papers we have counts for
5 papers · 1 filter
WALoMA: A Multitask Wireless Foundation Model via Adaptive Low-Rank Masked Autoencoders
Madi Makin, Asmaa Abdallah, Abdulkadir Celik +1
This paper proposes a multitask wireless foundation model via adaptive low-rank masked autoencoders (WALoMA), a unified multi-task foundation model for sixth-generation (6G) wirele…
Explainable Autoencoder Design for RSSI-Based Multi-User Beam Probing and Hybrid Precoding
Asmaa Abdallah, Abdulkadir Celik, Ahmed Alkhateeb +1
This paper introduces a novel neural network (NN) structure referred to as an ``Auto-hybrid precoder'' (Auto-HP) and an unsupervised deep learning (DL) approach that jointly design…
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…
ENWAR: A RAG-empowered Multi-Modal LLM Framework for Wireless Environment Perception
Ahmad M. Nazar, Abdulkadir Celik, Mohamed Y. Selim +3
Large language models (LLMs) hold significant promise in advancing network management and orchestration in 6G and beyond networks. However, existing LLMs are limited in domain-spec…
At the Dawn of Generative AI Era: A Tutorial-cum-Survey on New Frontiers in 6G Wireless Intelligence
Abdulkadir Celik, Ahmed M. Eltawil
The majority of data-driven wireless research leans heavily on discriminative AI (DAI) that requires vast real-world datasets. Unlike the DAI, Generative AI (GenAI) pertains to gen…