Delay Minimization Using Hybrid RSMA-TDMA for Mobile Edge Computing

Round 1

Reviewer 1 Report

The paper proposes a hybrid RSMA-TDMA scheme for mobile edge computing systems, where two edge users need to offload their task data to a MEC server. The offloading time is divided into two time phases, and a cognitive radio-inspired RSMA strategy is used in the first phase, while the remaining time is allocated to a single user to offload task data. The paper formulates an offloading delay minimization problem with power and energy constraints and develops an iterative algorithm by approximating the original problem into a convex one with Dinkelbach's method. The paper also establishes criteria for the three offloading methods and derives closed-form expressions for the optimal power allocation in different offloading methods.

Here are some suggestions to improve the paper:

- The paper could benefit from providing more context about the existing literature on the topic, especially regarding RSMA and TDMA. This would help readers better understand the novelty of the proposed approach and its contribution to the field.

- It is mentioned that the proposed scheme uses a cognitive radio-inspired RSMA strategy in the first time phase, but it does not provide details on what this strategy entails. It would be helpful to explain the strategy in more detail and provide insights into how it improves offloading delay.

- It is mentioned that the proposed approach considers power and energy constraints but does not provide clear explanations on what these constraints are or how they are modelled. It would be helpful to provide more detailed explanations of these constraints and how they affect the proposed approach.

- The paper presents numerical results comparing the proposed approach to existing offloading schemes, but the results are limited to scenarios with lower energy budgets. It would be helpful to present more comprehensive numerical results that cover a wider range of scenarios and provide insights into the robustness and limitations of the proposed approach.

- some related references are suggested to be used:

https://ieeexplore.ieee.org/abstract/document/9910565

https://ieeexplore.ieee.org/abstract/document/10012462

https://ieeexplore.ieee.org/abstract/document/9775597

https://ieeexplore.ieee.org/document/9887822

 

It would be helpful to proofread the manuscript carefully before submission to improve the overall readability and clarity of the paper.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Authors proposed an offloading delay minimization problem aiming to minimize overall offloading delay of the system with power and energy constraints. However, major corrections are required:

1.       Please provide a table in the related works section and comparison between present and exiting works.

2.       Contribution part is not clear. Please add the contribution of the work in the end of introduction as a bullet point.

3.       Network architecture NOT clear and should be revised.

4.       Task Computing delay is NOT considered. Please check this paper “Delay optimization in mobile edge computing: Cognitive UAV-assisted eMBB and mMTC services”.

5.       In Fig. 2, write down the title/caption of x-axis.

6.       In Fig. 3, write down the unit of x-axis (data size).

7.       Please find the complexity of proposed algorithm

8.       Please compared with previous algorithm in performance analysis

9.       It is recommended to use a professional proofread and native English correction.

 It is recommended to use a professional proofread and native English correction.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments are addressed

 

no more comments

Reviewer 2 Report

Thanks for correction. 

Well written.