ITU AI/ML Challenge Finale – Radio Resource Management (RRM) for 6G in-X Subnetworks

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  • Date
    25 August 2025
    Timeframe
    12:00 - 13:00 CEST
    Duration
    1 hours

    The Radio Resource Management (RRM) problems are usually formulated as an optimization problem with the aim of maximizing the average spectral efficiency of the network. There may be naturally occurring and malicious interference, with constraints in terms of maximum transmit power and energy consumption at the device and Access Point.

    Traditional optimization methods and heuristics have proven effective in certain contexts. However, the dynamic and complex nature of “In-X” subnetworks (e.g., in-vehicle, in-room communication) demands a more adaptive and data-driven approach, necessitating the adoption of advanced AI/ML solutions.

    The complexity of the operational scenario, characterized by unprecedented densities, makes heuristic approaches inefficient as they are designed for generic environments and conditions. This problem statement aims to use AI/ML techniques for an effective operational scenario.

    This challenge on “Radio Resource Management (RRM) for 6G In-X Networks” was hosted in 2024 with the aim of developing AI/ML-based centralized or distributed techniques for joint sub-band and power allocation in hyper-dense deployments for an industrial subnetwork.

    In today’s webinar, the winning solution of the challenge will be presented and felicitated, and further steps and research directions will be discussed.

    Learning Objectives: 

    • Recall the techniques for analysing Radio Resource Management (RRM) for wireless networks in general, the existing techniques, and their shortfalls
    • Compare with AI/ML-based techniques for an adaptive and data-driven approach to RRM
    • Evaluate the benefits of RRM in general and the upcoming AI techniques specifically
    • Question the techniques and discuss the answers.

    Recommended mastery level:

    • Basic understanding of wireless networks, the radio resource management problems in general
    • Basic understanding of the characteristics of the next generation wireless networks, such as 5G and 6G
    • Basic data analysis and ML modelling techniques

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