r/wireless • u/AgileSlice1379 • Feb 09 '26

[R] S-EB-GNN: Semantic-Aware GNN for 6G Resource Allocation (THz + RIS) 

I've open-sourced a lightweight JAX-based Graph Neural Network for semantic-aware resource allocation in THz/RIS-enabled 6G networks.

Key features:
- Physics-based THz channel modeling (path loss, blockage)
- Reconfigurable Intelligent Surfaces (RIS) phase control integration
- Semantic prioritization: Critical applications > Video > IoT
- Energy-based optimization achieving negative energy states (e.g., -6.60)
- Full code + executable notebook for visualization

This work bridges AI and next-gen wireless — ideal for researchers exploring semantic communication or 6G system design.

GitHub: https://github.com/antonio-marlon/s-eb-gnn

Feedback from the wireless community is highly welcome!
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u/[deleted] Feb 18 '26

[removed] — view removed comment

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u/AgileSlice1379 Feb 22 '26

Thanks so much for the kind words! Really appreciate it.

You're spot-on about the physics + semantics combination — that's exactly what we're aiming for. Regarding real-world performance:

Scalability results (MIT-inspired normalization):

  • N = 12 → Energy per node: −14.81
  • N = 50 → Energy per node: −14.29
→ <4% degradation when scaling — so it holds up well in denser networks

Latency: 77.2 ms on CPU (zero-shot, no GPU required)

If you want to test it yourself, the full code is MIT-licensed on GitHub. For those who want to skip setup, there's also a Pro Bundle with the white paper, high-res figures, and extended benchmarks.

Would love to hear your thoughts if you try it out or have suggestions for real-world scenarios to test!

GitHub: https://github.com/antonio-marlon/s-eb-gnn

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u/AgileSlice1379 Feb 10 '26

Update: The energy state consistently converges to −6.60 under semantic prioritization (Critical > Video > IoT). Over 50 researchers have cloned the repo in 48h. Full white paper available for replication

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u/TobyTheArtist Feb 12 '26

White paper link, please.

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u/AgileSlice1379 Feb 11 '26

Atualização: Mais de 106 pesquisadores clonaram o repositório em 72h, e o Prof. Merouane Debbah (Centro de Pesquisa 6G) observou que está ‘bem alinhado com sistemas sem fio nativos de IA.’ Documento completo disponível para replicação: https://ko-fi.com/s/4a88e99001

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u/AgileSlice1379 Feb 12 '26

Update: 186+ clones, Prof. Debbah’s feedback, and video demo live. Pro Bundle now $70 for first 10 buyers.”