PAPR Reduction in OFDM Signals by Self-Adjustment Gain Method
Round 1
Reviewer 1 Report
This is a sound work on one out of two inherent OFDM drawbacks PAPR and CFO. It would be good idea to involve the CFO in the model as well
Author Response
Comments by Reviewer 1-----------------------------------------------
Comment 1: This is a sound work on one out of two inherent OFDM drawbacks PAPR and CFO. It would be good idea to involve the CFO in the model as well.
Response: Thank you for this valuable comment. The CFO problem is another important issue in OFDM drawbacks. However, the effects of CFO are not taken into account in this study. The proposed method in this paper only focuses on, based on the ACE scheme, designing a simple and adaptive extension rule to reduce PAPR of OFDM signals with a fixed clipping threshold.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
The Abstract must be revised and improved, in order to be better correlated with the content of the paper and objectives. Authors should briefly address the obtained results.
Separate introduction (what are you solving here and why) and state of the art (what has been done in the sector).
The literature review is really not comprehensive. ONLY 21 items of random? selection? A very shallow overview of related methods were presented. Evenso, their description is not detailed enough. Referring to numeral items at once [3-8] is unacceptable. Please go over each reference and explain the relation to your work, the benefits and disadvantages of the method used, and mention the result achieved by other respectful authors.
I'd suggest adding an in-depth comparison to other works (in a comparative table format: method>application>dataset(conditions)>result).
Then there is a major problem with novelty. Self-adjusting gain adoption for peak power control is not a unique proposition... More technical novelty and contribution is expected from a journal paper.
The experimental overview is the weakest part of the paper. The experiments should be contextualized better (the reader should not be left to assume that they will get their own conclusions). Seems that only a hypothetical simulation was provided. Again what about real-life testing? Which scenario? At what actual applicable conditions?
Conclusions are basic and subjective. Rewrite, focusing only on statistically reliable data.
Author Response
Comments by Reviewer 2-------------------------------------------
Comment 1:
Separate introduction (what are you solving here and why) and state of the art (what has been done in the sector).
The literature review is really not comprehensive. ONLY 21 items of random? selection? A very shallow overview of related methods were presented. Evenso, their description is not detailed enough. Referring to numeral items at once [3-8] is unacceptable. Please go over each reference and explain the relation to your work, the benefits and disadvantages of the method used, and mention the result achieved by other respectful authors.
I'd suggest adding an in-depth comparison to other works (in a comparative table format: method>application>dataset(conditions)>result).
Response: Thank you for this valuable comment. The Introduction section is divided into several paragraphs as follows.
- For overall review on the literature, we already added more discussions for different PAPR reduction methods and provide a table (Table 1) to summarize the features for various schemes. (See the revised manuscript: Line 32-68.)
- For the ACE-based scheme, we review several methods related to our works in more details and give a comparison that initiate the motivation to develop the proposed method. (See the revised manuscript: Line 69-101.)
Comment 2: Then there is a major problem with novelty. Self-adjusting gain adoption for peak power control is not a unique proposition... More technical novelty and contribution is expected from a journal paper.
Response: Thank you for this valuable comment. The proposed scheme is motivated by the investigation on the ACE technologies that obtain considerable PAPR gains by the clipping strategy and the constellation extension rule by the optimization procedure for determining the specified rules in constellation extension, and is motivated by the adaptive filtering algorithm (RLS or Kalman filter) with the recursive gain that can diminish system errors by dynamically adjusting the measurements. Since the proposed scheme is optimal in Gaussian noise environment, the constellation extension rule will not cause the sharp deterioration in BER performance. Our simulation results verify the advantage. (See the revised manuscript: Line 94-113.)
Comment 3: Conclusions are basic and subjective. Rewrite, focusing only on statistically reliable data.
Response: Thank you for this valuable comment. the Simulation Results and Conclusion sections are already rewritten in more details and focus on the comparison with the related schemes. (See the revised manuscript: Line 265-281, Line 300-318, and Line 16-23.)
Author Response File: Author Response.pdf
Reviewer 3 Report
This was a very nicely written paper. The Abstract was succinct, the Introduction was clear, and the chosen Figures well articulated the thematics.
Author Response
Comments by Reviewer 3-------------------------------------------
Comment 1: This was a very nicely written paper. The Abstract was succinct, the Introduction was clear, and the chosen Figures well articulated the thematics.
Response: Thank you for your positive comments on our work
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
I'd like to thank authors for clarifications provided. However the novelty still remains questionable, I'd suggest further expanding the section on technical details as well as discussing alternatives and their effectiveness.
Author Response
Response: Thank you for this valuable comment. The technical discussions have been rewritten and given in the revised manuscript. (Line 89-123)
ACE based methods concern both the schemes for peaks-clipping and the criterions for constellation extension. By setting different clipping thresholds for varied PAPR levels, typical ACE techniques concentrate on the corresponding constellation adjustment. Moreover, optimum ACE technologies involve the trade-off between getting considerable PAPR reduction gains and complexity within reasonable BER or the trade-off between PAPR reduction and BER performance. To make the clipping and the constellation extension concurrently effective, it requires the optimization procedure to be performed iteratively to modify associated parameters till the required condition is satisfied.
Generally, the constellation extension rules in these optimum schemes maintain the conventional way, i.e., each clipped signal point is relocated to the new position according to the zone it drops and the extension criterion complied with. Obviously, these rules are constellation dependent. With the increase in the modulation order, these rules become complicated and must be carefully defined. Motivated by the observations the self-adjustment gain scheme is proposed to make the extension rule systematic and adaptable. The basic idea behind the proposed scheme is to measure the distance between the clipped signal point and its original location. It is possible to write an equation for the new assignment position by combing the clipped signal point with a displacement that is proportional to the measured distance with a proportionality constant defined as the self-adjustment gain (SAG). Motivated by the adaptive filtering algorithms such as the recursive least squares (RLS) or Kalman filter, the self-adjustment gain can be made as the ratio proportional to the reciprocal of the squared measurement distance and the clipping error power. Hence each signal point can be moved dynamically that will effectively smooth the clipped noise and diminish errors. Our simulation results verify the advantages.
Finally, the proposed self-adjustment gain scheme is a conceptual model that we try, from another perspective, to find a systematic and knowing way to define the constellation extension rule for PAPR reduction of OFDM signals. It also could play an active part in these optimum ACE based methods.
Author Response File: Author Response.pdf
Round 3
Reviewer 2 Report
Thank you for the verbal clarification of your approach. Unfortunatly, I cannot find the significant updates on the technical part of the paper, which leads to another marking of "Major revisions". I would strongly recommend providing full specifications (even droping generic mathematical formulas and reformulating on the exact issue) as well as straight UMLs as vizualization (activity and sequences diagrams).
Author Response
Thank you for this valuable comment. The technical derivations and discussions in Section 3 have been divided into several subsections in sequence and contents been rewritten in more details to clarify the proposed scheme in each step (Line 145-272). Besides, Figure 1 has been redrawn for corresponding to the rewritten contents. Figure 5 has redrawn to exhibit the step by step procedure of the proposed scheme. The rewritten part is enclosed for your reference.
Author Response File: Author Response.pdf
