IEEE Future Networks Artificial Intelligence and Machine Learning
Date: September 18, 2025
Time: 8:00 - 9:00 AM
Location: Virtual
ALLSTaR - Automated LLM-Driven Scheduler Generation and
Testing for Intent-Based RAN
Speaker: Dr. Maxime Elkael
The evolution toward open, programmable O-RAN and AI-RAN 6G networks creates unprecedented opportunities for Intent-Based Networking (IBN) to dynamically optimize RAN operations based on dynamic operators requirements. However, applying IBN effectively to the RANscheduler - a critical component determining resource allocation and system performance - remains a significant challenge. Current approaches predominantly rely on coarse-grained network slicing, lacking the granularity for dynamic adaptation to individual user conditions and traffic patterns. Despite the existence of a vast body of scheduling algorithms that could potentially translate high-level intents into executable policies, their practical utilization is hindered by implementation heterogeneity, insufficient systematic evaluation in production environments, and the complexity of developing high-performance scheduler implementations. This necessitates a more granular, flexible, and verifiable approach to align scheduler behavior with operator-defined intents. To address these limitations, ... Read More
PDH Certificate: while basic attendance is free, this course also offers one (1) Professional Development Hour (PDH) for a nominal fee; please choose the appropriate "Registration Fee" when registering; additional terms and conditions apply.
Register here:
https://events.vtools.ieee.org/m/489656