## 11 Conclusions
* The **ITU-R P.1546-6 model** showed poor terrain sensitivity and systematic underestimation, particularly in flat areas and in hilly or mountainous regions where the examined terrain is situated at a higher elevation than the base station. Its use should be limited to simple, large-scale estimates where fine terrain effects are negligible. * The **SUI model** performed poorly at 6 GHz, exhibiting low terrain correlation and strong underestimation across all terrain types. It is suitable only for rapid, low-complexity, conservative network planning where detailed terrain data is unavailable. * The **ITU-R P.452-17 model** maintained high terrain sensitivity and low prediction error in flat terrain at both frequencies. In more complex terrains at 6 GHz, it tended to moderately overestimate the field strength, which can be acceptable in interference-limited scenarios but reduces its precision for accurate coverage estimation. In conclusion, this analysis confirmed that prediction reliability, bias direction, and terrain sensitivity are all model- and frequency-dependent. Among the tested models, ITU-R P.452-17 remains the most practically applicable and computationally efficient alternative to deterministic methods, especially when realistic terrain influence must be considered without incurring the full computational burden of PEM, although its use should be carefully evaluated in complex terrains. These conclusions are indicated in Table 16.  
**Author Contributions:** Conceptualization, T.I.U. ; methodology, T.I.U. ; software, T.I.U. ; validation, T.I.U. ; formal analysis, T.I.U. ; investigation, T.I.U. ; resources, T.I.U. ; data curation, T.I.U. ; writing--original draft preparation, T.I.U. ; writing--review and editing, T.I.U. ; visualization, T.I.U. ; supervision, M.K. ; project administration, T.I.U. ; funding acquisition, T.I.U. All authors have read and agreed to the published version of the manuscript. **Funding:** This research received no external funding. **Data Availability Statement:** The data supporting the findings of this study are available within the article. Further inquiries can be directed to the corresponding authors. **Acknowledgments:** The author, [PERSON], gratefully acknowledges the support of the National Media and Infocommunications Authority of Hungary (NMHH), which provided a calm and supportive environment conducive to doctoral research, as well as access to essential software tools that facilitated the preparation of this work. Special thanks are due to [PERSON], Head of \begin{table}
\begin{tabular}{l l l l l l} \hline \hline
**Model** & **Terrain Sensitivity (\(r\))** & **Relative Error** & **Bias Direction** & **Reliability** & **Recommended Use** \\ \hline PEM & high (\(r>0.8\)) & reference (0\%) & neutral & excellent & reference model, AI \\ ITU-R P.1546-6 & low or negative & very high (40-630\%) & underestimation & weak & flat terrain, large-scale estimates \\ SUI & low (\(r<0.4\)) & high (65–220\%) & underestimation & weak & fast, low-complexity estimation \\ ITU-R P452-17 & high (\(r>0.9\)) & low (8–72\%) & mild overestimation & good–excellent & spectrum planning, \\ \hline \hline \end{tabular}
\end{table} 
Table 16: Summary of model characteristics based on terrain sensitivity, bias direction, and relative error. Unit, whose thoughtful leadership and encouragement created a workplace atmosphere marked by intellectual freedom and tranquility. I am also deeply indebted to [PERSON], Deputy Director General of NMHH, for his unwavering support and enduring interest in my academic journey from its inception. Finally, I am thankful to Szechenyi Istvan University and the Doctoral School of Multidisciplinary Engineering Sciences (MMTDI) for their financial contribution towards the publication of this paper. The authors declare no conflicts of interest.