Using Multi-Source Real Landform Data to Predict and Analyze Intercity Remote Interference of 5G Communication with Ducting and Troposcatter Effects

Round 1

Reviewer 1 Report

Figure 2 is cited before Figure 1. Figures should be numbered in order of citation.

Chinese characters remain in the flow chart shown in FIG. Please correct.

"As the propagation distance increases, the rotation of the plane of polarization also affects the link quality. Does the evaluation of propagation loss in this paper consider the effect of rotation of the plane of polarization? If you decide that the evaluation is not necessary, please indicate the reason." In addition, please correct the following sentences that have already been reported as follows. Before: "Chinese characters remain in the flow chart shown in FIG. Please correct." After: "Chinese characters remain in the flow chart shown in Figure 7. Please correct."

 

Author Response

Dear Reviewer:

We appreciate it very much for your positive and constructive comments on our manuscript. We have revised the manuscript in accordance with your comments. Please see the attachment for our description on the revision.

Author Response File: Author Response.pdf

Reviewer 2 Report

Only minor editing is required. In some instances, i.e. Section 4, figures are several pages back from where they are referred to in the text - it might be a good idea to move them if possible.

Author Response

Dear Reviewer: 

Thanks a lot for your good suggestion. We have reorganized the figures in Section 4. And corresponding introductions of Figures are added in the text before figures. The corresonding revisions are highlighted in the PDF version of manuscript.  Please see the attachment for the revision of manuscript.

Author Response File: Author Response.pdf

Reviewer 3 Report

The main contribution of this paper is the analysis of intercity remote interference of 5G with real landform data, on top of that, reasonable prediction is also discussion. The results obtained will be useful for 5G study. In terms of experimental technique, this paper is conventional. The analysis methodologies including deep learning model prediction are suitable. I am pleased to recommend this paper to be published.

Author Response

Dear Reviewer:

Thank you very much for your suggestion and recommendation of our manuscript entitled "Using Multi-source real landform data to predict and analyze intercity remote interference of 5G communication with ducting and troposcatter effects" (ID: remotesensing-1850503). We would continue to make in-depth research in this ducting propagation and AI prediction area.