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Peer-Review Record

Joint Trajectory and Communication Design for Buffer-Aided Multi-UAV Relaying Networks

Appl. Sci. 2019, 9(24), 5524; https://doi.org/10.3390/app9245524
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Appl. Sci. 2019, 9(24), 5524; https://doi.org/10.3390/app9245524
Received: 3 November 2019 / Revised: 30 November 2019 / Accepted: 12 December 2019 / Published: 15 December 2019
(This article belongs to the Section Electrical, Electronics and Communications Engineering)

Round 1

Reviewer 1 Report

Introduction should be revised to correct typos and some grammatical errors. 

Regarding technical aspects there are some details that should be clarified and which are:

-The authors do not mention if the proposed algorithm can be extended to Rayleigh fading channels and what happens if for some reason the UAVs are not in line of sight?

- In eqs (15a) and (15b) the notation is not clear. Could the authors clarify this aspect? The same is still valid for equations (16a) and (16b) and (23a) to (23h).

 - In eq (25a) what means tk,d[n]?

-The first order Taylor expansion given by eq. (26) should be clarified since it is not obvious.

- How it is assured that UAVs satisfy always the collision avoidance constrains all the time slots if they are totally autonomous?

- What is the complexity associated to the proposed algorithms and the increase on complexity when compared with other algorithms with same purpose? 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

The proposed technique derives the state change of the information in the buffer of UAV relays and maximizes the end-to-end average throughput by jointing the relay selection, UAV transmit power and UAV trajectory optimization.

Furthermore, authors also present an efficient iterative algorithm based on the block coordinate descent and the successive convex optimization technique in order to deal with a mixed integer non-convex optimization problem. The simulation results show that by alternately optimizing the relay selection, UAV transmit power and UAV trajectory, the proposed algorithm is able to achieve convergence quickly.

This work presents some good points but it also has some flaws.

The authors keep on stating that the channel models between UAVs and ground nodes is modeled as Rician. However, other possible models could be used. Is the choice of the Rician model something common in this scenario? The authors should provide some more comments or references to support this decision.

Fig. 1 is commented as "System model" and buffer-aided. In my opinion this figure does not describe the authors problem. It is a very simple scheme that could be used is any work that involves drone communication. Where and how does the buffer come into play? Please, add some more detail to this figure.

The idea of decomposing the optimization problem into two convex sub-problems is nice and well-described. However, some clarifications are necessary.

The sentence "to solve the integer constraints, we relax the binary variables in (8) into continuous variables, i.e., 0 ≤ ak,m [n] ≤ 1" is not clear to me. If ak,m represent the communication or not, it should be reasonable that these are binary variables. What is the physical meaning of relaxing them into continuous variable?

The overall algorithm convergence should be revised. Through a series of inequalities the authors prove that "the objective value of problem (16) is upper bounded of a finite value, therefore, the proposed algorithm converges." Actually, this does not prove the convergence. Please, revise this section.

Numerical results are nice and easy to follow but they do not provide any comparison at all. In the abstract the authors state "the proposed algorithm is able to achieve convergence quickly and significantly improve the average throughput,as compared to other benchmark schemes" but in the numerical results section I cannot find any comparison. Please, add this in the next version of the paper. Furthermore, what about the convergence time of your algorithm ? Is it computationally heavier/lighter than other SOA schemes ?

Finally, as minor considerations, please fix some typos (e.g. the word "finial" --> "final").

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

My questions and concerns were clarified by the authors, and the problems identified in previous versions are absent in this revised version. I do not have more sugestions for corrections our improvements.  

Reviewer 2 Report

The authors have addressed the majority of my concerns.


The paper quality is significantly improved and therefore I suggest to accept the manuscript. Please find below some final comments.


The authors confirm in their cover letter that they were not able to compare their work with other SOA algorithms. This is due to fact that , to the best of their knowledge, two buffer-assisted UAV has been introduced only recently. Therefore, I suggest to remove from the paper the expression "comparison with other benchmark schemes" since there is no comparison with other scheme but just with different scenarios.


In the cover letter the authors also provide a good answer to the issue of relaxing the binary variables in into continuous variables. Please put some explanation also in the paper to help the readers.

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