# UAV Dynamic Non-Terrestrial Transmission Channel Analysis Based on SSCM-RT Model
## 5 Conclusions  
This paper proposes a hybrid spatial statistical ray tracing (SSCM-RT) channel model to cope with long-distance and dynamic communication problems in the non-terrestrial transmission channels of a high altitude, as is the case for UAVs. The spatial statistical channel model provides the parameters to simulate and evaluate the model's performance using frequencies in the range from 28 GHz to 55 GHz. We achieved an error value due to the combined path loss using the SSCM-RT model not exceeding 2 dB. Moreover, the segmentation approach used to model path loss using the hybrid technique reduces the complexity of simulations compared to a full RT model. However, the type and number of rays remain the same. We demonstrated the validity of the SSCM-RT hybrid channel modeling scheme based on path loss given a fixed number of rays in a symmetric scenario. We examine the impact of spatial consistency of the channel model by simulating the relative motion of the UAVs using a Gauss-Markov model and a random direction model. The measurement of channel properties can be made to fit realistically and show a smooth evolution with the introduction of spatial consistency. The SSCM-RT hybrid model with the introduction of spatial consistency is also suitable for dynamic scenarios with irregular distance changes and can maintain spatial consistency during the whole motion process. The reliability of the SSCM-RT hybrid channel modeling scheme is further demonstrated based on the spatial consistency in asymmetric dynamic scenarios. Methodology, J.Y. ; Software, H.X. ; Validation, Z.P. ; Data curation, Y.Z. ; Writing--original draft, H.X. ; Writing--review & editing, J.Y. All authors have read and agreed to the published version of the manuscript. This research received no external funding. **Data Availability Statement:** No new data were created. **Conflicts of Interest:** The authors declare no conflict of interest. Figure 13: The path loss of two motion models by using SSCM-RT model. (**a**) Gauss–Markov model; (**b**) random direction model. * (13) [PERSON]; [PERSON]; [PERSON] UAV/HAP-Assisted Vehicular Edge Computing in 6G: Where and What to Offload? In Proceedings of the 2022 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit), Grenoble, France, 7-10 June 2022; pp. 178-183. [CrossRef]
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