edge features 1graph neural networks 1learning to optimise 1mixed-integer linear programming 1relay selection 1vehicular communications 1
From the 1 of 2 papers with an AI index.
2 papers
cs.AI2026
AI-Driven Multi-Hop Relay Selection for Smart Urban NR-V2X Networks via Learning-to-Optimize Graph Neural Networks
Giambattista Amati, Federica Mangiatordi, Simone Angelini +2
Reliable and low-latency NR-V2X communications are essential for smart mobility in dense urban environments. However, limited Road-Side Unit (RSU) density, frequent non-line-of-sig…
cs.LG2026
Low-Latency Relay Selection in NR-V2X Vehicular Communications via Graph Isomorphism Networks with Edge Features
Giambattista Amati, Federica Mangiatordi, Emiliano Pallotti +3
The paper proposes a graph‑neural‑network approach (GINE) to select relay nodes for low‑latency NR‑V2X communications, using edge features and an offline MILP oracle to train the m…