Intent-Aware DRL-Based Uplink Dynamic Scheduler for 5G-NR

no code implementations • 27 Mar 2024 • Salwa Mostafa, Mateus P. Mota, Alvaro Valcarce, Mehdi Bennis

We investigate the problem of supporting Industrial Internet of Things user equipment (IIoT UEs) with intent (i. e., requested quality of service (QoS)) and random traffic arrival.

Scheduling

Intent Profiling and Translation Through Emergent Communication

no code implementations • 5 Feb 2024 • Salwa Mostafa, Mohammed S. Elbamby, Mohamed K. Abdel-Aziz, Mehdi Bennis

Instead, a framework based on emergent communication is proposed for intent profiling, in which applications express their abstract quality-of-experience (QoE) intents to the network through emergent communication messages.

Self-Learning Translation

Emergent Communication Protocol Learning for Task Offloading in Industrial Internet of Things

no code implementations • 23 Jan 2024 • Salwa Mostafa, Mateus P. Mota, Alvaro Valcarce, Mehdi Bennis

In this paper, we leverage a multi-agent reinforcement learning (MARL) framework to jointly learn a computation offloading decision and multichannel access policy with corresponding signaling.

Multi-agent Reinforcement Learning reinforcement-learning