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ntn

End-to-end ns-3.43 simulator for 6G non-terrestrial networks. Five integrated modules: 3GPP Rel-17 TTE-aware Conditional Handover, O-RAN Near-RT + Space RIC with 13 xApps, sub-THz/THz physics (HITRAN, UM-MIMO, RIS, ISAC), ns3-ai fork with federated learning, NTN traffic — over SNS3, mmWave-NR, 3GPP TR 38.811. LEO/MEO/GEO.

Modernised fork of ns3-ai (Yin et al., WNS3 2020): ns-3.43 + Python 3.13 + NumPy 2 + Gymnasium 1.0 compatibility patches for the shared-memory C++/Python bridge. Adds NTN Gym environments and a Flower AI federated-learning adaptor (FedAvg/Prox/Nova/SCAFFOLD). Upstream credit preserved in AUTHORS.md. GPL-2.0.

Sub-THz/THz physics module for ns-3.43 NTN scenarios — 100 GHz to 1 THz. HITRAN-2020 line-by-line absorption, ITU-R P.835/676/618/838 channels, D-band ISL, UM-MIMO up to 16384 elements, RIS quantisation sweep, ISAC CRB, EKF beam tracker, LEO-pass demos. Cross-validated against ITU-R P.676-13 and am. GPL-2.0.

Space O-RAN reference implementation for ns-3.43: Near-RT RIC + Space RIC, 13 xApps, A1 policy engine (11 policies), E2SM-RC runtime (28 actions), 5 conflict-resolution strategies and 4 federated-learning aggregators (FedAvg/Prox/Nova/SCAFFOLD). Validated 60-s LEO run: 7369 actions, 0 conflicts. GPL-2.0.