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Dynamic D2D-Assisted Federated Learning over O-RAN: Performance Analysis, MAC Scheduler, and Asymmetric User Selection
v1v2 (latest)

Dynamic D2D-Assisted Federated Learning over O-RAN: Performance Analysis, MAC Scheduler, and Asymmetric User Selection

9 April 2024
Payam Abdisarabshali
Kwang Taik Kim
Michael Langberg
Weifeng Su
Seyyedali Hosseinalipour
ArXiv (abs)PDFHTMLGithub

Papers citing "Dynamic D2D-Assisted Federated Learning over O-RAN: Performance Analysis, MAC Scheduler, and Asymmetric User Selection"

2 / 2 papers shown
From Federated Learning to X-Learning: Breaking the Barriers of Decentrality Through Random Walks
From Federated Learning to X-Learning: Breaking the Barriers of Decentrality Through Random Walks
Allan Salihovic
Payam Abdisarabshali
Michael Langberg
Seyyedali Hosseinalipour
FedMLOOD
354
0
0
03 Sep 2025
Multi-Modal Multi-Task Federated Foundation Models for Next-Generation Extended Reality Systems: Towards Privacy-Preserving Distributed Intelligence in AR/VR/MR
Multi-Modal Multi-Task Federated Foundation Models for Next-Generation Extended Reality Systems: Towards Privacy-Preserving Distributed Intelligence in AR/VR/MR
Fardis Nadimi
Payam Abdisarabshali
Kasra Borazjani
Jacob Chakareski
Seyyedali Hosseinalipour
555
5
0
06 Jun 2025
1
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