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Peer-Review Record

RIS-Assisted Network Slicing Resource Optimization Algorithm for Coexistence of eMBB and URLLC

Electronics 2022, 11(16), 2575; https://doi.org/10.3390/electronics11162575
by Xianhao Shen, Ziling Zeng and Xin Liu *
Reviewer 1: Anonymous
Reviewer 2:
Electronics 2022, 11(16), 2575; https://doi.org/10.3390/electronics11162575
Submission received: 2 August 2022 / Revised: 11 August 2022 / Accepted: 12 August 2022 / Published: 17 August 2022

Round 1

Reviewer 1 Report

I have no further comments.

Author Response

Thank you again for your previous constructive comments. You can tell us if there is anything that needs to be changed afterwards.

Reviewer 2 Report

Article is well written. If possible. authors may try adding a few more graphs in the results.

Author Response

Thanks for your valuable suggestions! We have revised our manuscript referring to your comments. Please see the attached file.

 

Author Response File: Author Response.pdf

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.


Round 1

Reviewer 1 Report

First line in the abstract is gramatically incorrect.

Second line starts with And which is again incorrect.

Authors should correct the paper gramatically and try resubmitting.

 

Reviewer 2 Report

The authors considered a RIS-aided eMBB and URLLC network slice resource allocation. I have the following major concerns:

1. Firstly, the manuscript is poorly written and therefore it is quite difficult to understand various descriptions.

2. The motivation for the work is not clear and thus the novelty is an issue.

3. The use of RIS is also irrational. For URLLC, it is desirable to have the minimum hops of transmission. However, using RIS would require two-hop transmission whose phase shifts design also increase the latency.

4. Why do the authors consider a heuristic approach to solve the optimization? what about its complexity compared with other baseline or more advanced convex optimization techniques.

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