Mohamed Sana | DeepAI

DeepAI AI Chat

Featured Co-authors

Wei Yu
78 publications
Emilio Calvanese Strinati
18 publications
Antonio De Domenico
15 publications
Mattia Merluzzi
5 publications
Mickael Maman
4 publications
Nicola di Pietro
3 publications
Esteban Catté
3 publications
Benoit Miscopein
1 publication
Yves Lostanlen
1 publication

∙ 08/04/2023

Semantic Channel Equalizer: Modelling Language Mismatch in Multi-User Semantic Communications

We consider a multi-user semantic communications system in which agents ...

0 Mohamed Sana, et al. ∙

∙ 06/30/2023

Federated Multi-Agent Deep Reinforcement Learning for Dynamic and Flexible 3D Operation of 5G Multi-MAP Networks

This paper addresses the efficient management of Mobile Access Points (M...

0 Esteban Catté, et al. ∙

∙ 03/09/2023

Dual-Attention Deep Reinforcement Learning for Multi-MAP 3D Trajectory Optimization in Dynamic 5G Networks

5G and beyond networks need to provide dynamic and efficient infrastruct...

0 Esteban Catté, et al. ∙

∙ 02/15/2023

Learning Hierarchical Resource Allocation and Multi-agent Coordination of 5G mobile IAB Nodes

We consider a dynamic millimeter-wave network with integrated access and...

0 Mohamed Sana, et al. ∙

∙ 05/03/2022

Cost-Efficient and QoS-Aware User Association and 3D Placement of 6G Aerial Mobile Access Points

6G networks require a flexible infrastructure to dynamically provide ubi...

0 Esteban Catté, et al. ∙

∙ 10/14/2021

Learning Semantics: An Opportunity for Effective 6G Communications

Recently, semantic communications are envisioned as a key enabler of fut...

0 Mohamed Sana, et al. ∙

∙ 06/04/2021

Transferable and Distributed User Association Policies for 5G and Beyond Networks

We study the problem of user association, namely finding the optimal ass...

0 Mohamed Sana, et al. ∙

∙ 03/31/2021

Energy Efficient Edge Computing: When Lyapunov Meets Distributed Reinforcement Learning

In this work, we study the problem of energy-efficient computation offlo...

0 Mohamed Sana, et al. ∙

∙ 06/16/2020

Multi-Agent Reinforcement Learning for Adaptive User Association in Dynamic mmWave Networks

Network densification and millimeter-wave technologies are key enablers ...

0 Mohamed Sana, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world