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New RAN-JEPA model optimizes energy efficiency in 5G networks

By PulseAugur Editorial · [2 sources] ·

Researchers have developed RAN-JEPA, a novel action-conditioned world model designed for energy-efficient mobile network control. This model addresses the challenge of scarce intervention data by first learning a predictive latent representation from abundant passive telemetry, then adapting it to specific domains. Finally, it learns action-conditioned dynamics from limited controlled trajectories, demonstrating lower prediction error than GPT-2 and mechanistic baselines in simulations and achieving higher sleep ratios in a 5G testbed. AI

IMPACT This research could lead to more energy-efficient mobile network operations through advanced AI control.

RANK_REASON Academic paper detailing a new model and its evaluation.

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New RAN-JEPA model optimizes energy efficiency in 5G networks

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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Binghan Wu, Kai Zeng, Kai Yang, Ya-Qin Zhang, Joseph Sifakis, Ye Ouyang ·

    RAN-JEPA: An Action-Conditioned World Model for Energy-efficient Mobile Network Control

    arXiv:2610.17584v1 Announce Type: new Abstract: Operational mobile networks are rich in observations but poor in interventions: they continuously generate large volumes of passive telemetry, while controlled action--response trajectories remain comparatively scarce and costly to …

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    RAN-JEPA: An Action-Conditioned World Model for Energy-efficient Mobile Network Control

    Operational mobile networks are rich in observations but poor in interventions: they continuously generate large volumes of passive telemetry, while controlled action--response trajectories remain comparatively scarce and costly to collect. This observation--intervention asymmetr…

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