Automatic Modulation Recognition Based on the Optimized Linear Combination of Higher-Order Cumulants
Round 1
Reviewer 1 Report
Authors provided clear motivation and contribution of the proposed study. The whole manuscript is well-structed and readable.
The presented algorithm shows high accuracy for the modulation schemes even at lower SNRs during simulation scenarios. I would expect to see furthermore the performance of algorithm on application scenarios.
Author Response
Thankyou so much for highlighting issues in our manuscript and we have updated the file.
Author Response File: Author Response.pdf
Reviewer 2 Report
Dear Authors,
I think the paper in general is good, but some comments need to be considered to improve the content of the paper. The following are my comments:
1- The introduction needs to be improved to cover the topics in this paper.
2- Related works section is perfect.
3- show samples in plots for each phase of the system like parameter Extraction (HOC), ...etc.
4- You mentioned that data is separated into 70% for training and 20% for testing. Where is the missed 10% is it used for evaluation?
5- GA based Optimal Weight Finder algorithm error plot with generations or iterations.
6- show a scatter plot for extracted features to see If there can discrimination between different classes.
7- what is the setting for the KNN classifier?
8- Show a detailed Proposed System Model, the recognized is missed in the graph.
Author Response
Thankyou for kind suggestions to update the manuscript. We have properly update the manuscript.
Author Response File: Author Response.pdf