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Tests on realistic cross-border FM coordination scenarios show that the clustering strategy greatly reduces optimisation complexity and runtime while maintaining foreign-service protection and domestic coverage, and yields an interpretable ranking of transmitters that contribute most to harmful interference, supporting...
This paper argues that the Learning-to-Optimize (L2O) represents the missing architectural layer between optimisation and AI-native intelligence, and establishes L2O as an architectural abstraction applicable across heterogeneous communication and computing systems.
A Learning-to-Optimise (L2O) framework based on Graph Neural Networks (GNNs) for real-time NR-V2X relay selection that achieves connectivity comparable to that of the MILP oracle while reducing execution time by orders of magnitude.
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