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Towards Robust Stability Prediction in Smart Grids: GAN-based Approach under Data Constraints and Adversarial Challenges
In particular, data scarcity is a key issue: obtaining grid instability instances is tough due to the need for significant expertise, resources, and time.
Interference Distribution Prediction for Link Adaptation in Ultra-Reliable Low-Latency Communications
Motivated by the fact that most of the URLLC use cases with most extreme latency and reliability requirements are characterized by semi-deterministic traffic, we propose to exploit the time correlation of the interference to compute useful statistics needed to predict the interference power in the next transmission.
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