Novel Intelligent Methods for Channel Path Classification and Model Determination Based on Blind Source Signals

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript entitled “Research on intelligent channel path classification and model determination methods based on blind source signals” by Cao et al. is found to be very interesting in scientific view.

I have some queries regarding the modification of the manuscript. Though the manuscript is well written but I think the manuscript still have some correction need for the publication in the reputed journal like atmosphere.

 

Title:

Research on intelligent channel path classification and model determination methods based on blind source signals

Can you make it more interesting it ??

Can you please describe that blind and unknown sources are different??

 “Propagation channel path classifying and modelling for wireless signals is a key fundamental issue in wireless systems. It is an important aspect to radio wave propagation research and wireless applications.” : Rephrase these two lines. Or combine these lines.

Line 68-69: “In this paper, new intelligent propagation path classification, channel model discrimination method for blind source is investigated.”

Why it is needed to be investigated. Put some proper objective for the purpose of the work.

·       Put the Table 3 and 4 as text not as programme for reader interest.

·       Can you put a proper scientific approach where these model can be used just for verification purpose??

·       Put a discussion.

 

·       Proper conclusion needed.

Comments on the Quality of English Language

Moderate editing of English language required.

Author Response

Dear reviewer,

 

Thank you for your suggestions and constructive comments on our manuscript. We have carefully considered the suggestions and made some changes. Sentence revisions are marked in yellow, other changes are marked in green. Please see the attachment, this is the revised manuscript.

 

Revision notes, point-by-point, are given as follows:

 

Comment 1: Moderate editing of English language required.

Reply:

Thank for your suggestion. We have optimized and modified the article for statements and errors in the revised manuscript and marked it in yellow. These changes will not influence the content and framework of the paper. We appreciate for your warm work earnestly and hope that revised manuscript could be acceptable for you.

 

1. Modify “modelling” to “modeling”. (4 in total. row 53,54,335,357)
2. Modify “discrimination” to “determination/determined” to enhance the consistency of the paper. (row 78,246,247,307,309)
3. Revision of tense inconsistencies in some statements.

 

Comment 2: The title “Research on intelligent channel path classification and model determination methods based on blind source signals”, Can you make it more interesting?

Reply:

We have made the following changes to the title of the article.

 

Modified to:

“Novel intelligent methods for channel path classification and model determination based on blind source signals”

 

Comment 3: Can you please describe that blind and unknown sources are different?

Reply:

In a broader sense we can think of blind and unknown sources as meaning the same thing. But they have subtle differences in the field of signal processing.

The word “blind” comes from “blind source separation (BSS)” in the signal process, it refers to signals that are mixed together but the mixing process is known. BSS is commonly used in audio and image processing applications.

Unknown sources refer to signals that are completely unknown and have no known characteristics or parameters.

In the article, we know the mechanisms of FM, and want to know the position and other characteristics of it, so it is suitable to call “blind source”.

 

Comment 4: “Propagation channel path classifying and modelling for wireless signals is a key fundamental issue in wireless systems. It is an important aspect to radio wave propagation research and wireless applications.” Rephrase these two lines. Or combine these lines.

Reply:

In these two sentences, we would like to express the importance of this work in scientific research and practical applications. We rewrote this sentence a bit more succinctly.

 

Modified to:

“The channel path classification and model determination of electromagnetic wave propagation play a crucial role in wireless system applications and relevant research.”

 

Comment 5: Line 68-69: “In this paper, new intelligent propagation path classification, channel model discrimination method for blind source is investigated.” Why it is needed to be investigated. Put some proper objective for the purpose of the work.

Reply:

We have improved the Introduction Section. (The logic of the second part is enhanced and the purpose of the proposed method is explained).

 

Modified to:

“

…Therefore, in order to simplify the scenarios of channel research, meet the new scenarios of future radio applications, and explore the possibility of blind source channel modeling, this paper puts forward a new method.

Based on this, novel intelligent methods for channel path classification and model determination based on blind source signals are investigated. The specific sections are as follows: Section 2 presents the theory for propagation channels path classification and models determination. Section 3 presents the localization method, the channel path classification method and the verification measurement system established to obtain the required data. Section 4 illustrates the results of the analysis of the FM measurements at 92.7 MHz and 95.6 MHz, which validates the method proposed in this paper. Section 5 gives the conclusions and prospect.”

 

Comment 6: Put the Table 3 and 4 as text not as program for reader interest.

Reply:

We have put the tables as text.

 

Table 3 modifies to:

 “

(1)  Get all the paths and the first Fresnel zone of the receiving point and the source transmitting point.

(2)  If there is a blocker such as a building on this path, the channel is a NLoS channel (without direct path).

(3)  If there is no blocker in the first Fresnel zone, it is a LoS channel (only the direct path).

(4)  If there is a blocker in the first Fresnel zone, but not blocking the direct link between Tx and Rx, then it is a multi-LoS channel (the direct and non-direct path).

 

Table 4 modifies to

 “

(1) Get single standard parabolic equation, Egli, Okumura-Hata model’s data.

(2) The three models are used as the center to extend the domain radius outward, and the data within the radius of the connected neighborhood is of the same model.”

 

Comment 7: Can you put a proper scientific approach where these models can be used just for verification purpose? Put a discussion.

Reply:

We added Section 4.5 and discussed the generalizability of the approach, giving an example for supporting it.

 

Modified to:

“

4.5. Discussion

The focus of this subsection is to analyze the three channel types from the transmitting point to the receiving point, as well as the modeling of propagation in urban areas. The presence of multiple modes highlights the complexity of radio wave propagation in urban areas, and the proposed method can be applied to a wide range of fields. For example, the method can find applications in the field of atmospheric inversion. By capturing the signal source, it is possible to localize it and analyze its propagation mode and atmospheric environment. By utilizing the proposed techniques, the accuracy of atmospheric inversion can be improved, leading to better understanding and analysis of atmospheric conditions [38].”

 

Comment 8: Proper conclusion needed.

Reply:

We have rewritten the conclusion to make it clearer. (It is divided into three paragraphs, the first of which is intended to illustrate the summary of this paper, and the second to show the fields in which this paper can make a difference.)

 

Modified to:

“

In this paper, a new intelligent channel path classification method and channel modeling method are proposed to address the complexity of the urban electromagnetic environment and the challenge of blind source constraints. The hybrid intelligent method, combining the particle swarm algorithm and genetic algorithm, is used for blind source localization to obtain the location and transmit power information of the radiated source.

A mobile measurement system is constructed based on ambient radio signals, and the proposed method is validated through a comprehensive study using FM band signals at 92.7 MHz and 95.6 MHz. The study analyzes different channel types including LoS, multi-LoS, and NLoS channels. Additionally, propagation models applicable to test point propagation are examined. The proposed method successfully distinguishes the channel types between transmitting and receiving points, and demonstrates that the broadcast signal propagation model closely aligns with the actual spatial propagation characteristics of radio waves. These results confirm the method's effectiveness proposed in this study and suggest the feasibility of using a propagation characterization method based on blind source signals.

Furthermore, statistical models of urban areas are provided to further characterize the propagation properties based on the measured data. Looking ahead, the field of mobile communication is expected to make new breakthroughs in artificial intelligence and big data. The system presented in this paper can be utilized to confirm the propagation channel path and model the propagation characteristics of future signals in higher frequency bands [39-40].”

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

There are a few comments on the layout of the article:

1. all figures and tables should be cited in the main text as Figure 1, Table 1, Table 2, etc. (none fig.2, tab.1 etc.);

2. in mathematical expressions brackets should cover the entire fraction as shown below (Equation 8 is an example):

;

3. the text following an equation need not be a new paragraph (rows: 102, 128, 144, 149,163, 175, 190, 192, 193);

4. equation 11 should look as follows:

.

 

Comments on the Quality of English Language

In general, the translations to the English seems good. The introduction and conclusion are written in good clear English, but there are some problems in the main text of the article. First of all, there are not tenses  matching up in sentences sometimes. In some sentences it is not clear what the authors meant so the authors should work on the text further to make it sound more definitely. In particular, the presence of necessary verbs in the sentences and the relevance of using the future tense needs check. In addition, I draw attention to the caption to Figure 6 (lines 296-298) as it should be rewritten to make it clearer.

Author Response

Dear reviewer,

 

Thank you for your suggestions and constructive comments on our manuscript. We have carefully considered the suggestions and made some changes. Sentence revisions are marked in yellow, other changes are marked in green. Please see the attachment, this is the revised manuscript.

 

Revision notes, point-by-point, are given as follows:

 

Comment 1: There are some problems in the main text of the article. First of all, there are not tenses matching up in sentences sometimes. In some sentences it is not clear what the authors meant so the authors should work on the text further to make it sound more definitely

Reply:

Thank for your suggestion. We have optimized and modified the article for statements and errors in the revised manuscript and marked it in yellow. These changes will not influence the content and framework of the paper. We appreciate for your warm work earnestly and hope that revised manuscript could be acceptable for you.

 

1. Modify “modelling” to “modeling”. (4 in total. row 53,54,335,357)
2. Modify “discrimination” to “determination/determined” to enhance the consistency of the paper. (row 78,246,247,307,309)
3. Revision of tense inconsistencies in some statements.

 

Comment 2: all figures and tables should be cited in the main text as Figure 1, Table 1, Table 2, etc. (none fig.2, tab.1 etc.)

Reply:

We have added the missing references of the figures and tables in the article, and revise to “Figure/Table”.

(row 91,96,107,196,222,224,258,304,306,314,322,323,327,333,339,342)

 

Comment 3: in mathematical expressions brackets should cover the entire fraction as shown below (Equation 8 is an example):

Reply: We have modified the brackets in Eq. 8 and Eq. 9.

 

Comment 4: the text following an equation need not be a new paragraph (rows: 102, 128, 144, 149,163, 175, 190, 192, 193);

Reply: Thank you for pointing out the error, we have removed the indentation after equations. (row 109,137,153,157,158,168,173,185,217,219,220)

 

Comment 5: equation 14 should look as follows:

L=57.54+25.64log(r)+25.64log(r)+1.55

Reply: Thank you for the suggestion, we have updated all formulas with “log” instead of “lg”. (Equation 2,3,4,5,6,13,14)

 

Comment 6: The caption of figure 6 (lines 296-298) should be rewritten to make it clearer.

Reply:

We rewrote the caption of Figure 6 and put the explanation to the section 4.3. (lines 315-317)

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The work is focused on the study and identification of channels using blind search algorithms. The work is interesting and provides some results that may be of interest to the research community. However, before publication, the authors should take into account the following sugggestions:

- Check English, because there are same typos... modelling/modeling...

- Improve the last paragraph of the Introduction Senction. 

- More references should be included in the firts part of the Introduction Section.

- Firs paragraph on page 3, after Figure 1, line 4: ... of these channels, write "... of these contributions"

- Do not indent the text after equations when the parameters are being described. 

- First paragraph of Subsection 2.2.2, the validityof the Okumura-Hata model is 150-1500 MHz.

- Check equation 4.

- Provide references related to the particle swarm algorithm in Section 3.1 and expline the parameters of Table 1, and justify their value. 

- In equation (12), is the radiation pattern of the tx-antenna considered? If not, explain its impact on the results. 

- In Subsection 4.1, the authors indicate that the local received signal needs to be in the range of 20-40 \lambda. If the authors are refering to the small-local fading, the stationaty of the channel  also depends on the defree of heterogeneity of the environment,  and the range may be wider. Please, explain this in the manuscript.

- In Figure 4 the map of the terrain must be appear as a primary layer. 

- Check firts column of Table 6.

- Figure 7 better the distance in log-scale, showing the linear relation between the path loss (in dB) and the distance. Write correctly the x and y lables: Loss (dB) instead of Loss/dB.

 

Comments on the Quality of English Language

Check English because there are some typos.

Author Response

Dear reviewer,

 

Thank you for your suggestions and constructive comments on our manuscript. We have carefully considered the suggestions and made some changes. Sentence revisions are marked in yellow, other changes are marked in green. Please see the attachment, this is the revised manuscript.

 

Revision notes, point-by-point, are given as follows:

 

Comment 1: Check English, because there are same typos... modelling/modeling...

Reply: Thank for your suggestion. We have optimized and modified the article for statements and errors in the revised manuscript and marked it in yellow.

 

1. Modify “modelling” to “modeling”. (4 in total. row 53,54,335,357)
2. Modify “discrimination” to “determination/determined” to enhance the consistency of the paper. (row 78,246,247,307,309)
3. Revision of tense inconsistencies in some statements.

 

Comment 2: Improve the last paragraph of the Introduction Section.

Reply:

We have improved the Introduction Section. (The logic of the second part is enhanced and the purpose of the proposed method is explained).

 

Modified to:

“

…Therefore, in order to simplify the scenarios of channel research, meet the new scenarios of future radio applications, and explore the possibility of blind source channel modeling, this paper puts forward a new method.

Based on this, novel intelligent methods for channel path classification and model determination based on blind source signals are investigated. The specific sections are as follows: Section 2 presents the theory for propagation channels path classification and models determination. Section 3 presents the localization method, the channel path classification method and the verification measurement system established to obtain the required data. Section 4 illustrates the results of the analysis of the FM measurements at 92.7 MHz and 95.6 MHz, which validates the method proposed in this paper. Section 5 gives the conclusions and prospect.”

 

Comment 3: More references should be included in the first part of the Introduction Section.

Reply:

We have added references in the introduction section, plus some literature that fits the topic in the rest of the article for support of my work.

 (references 2,3,4,5,23,24,25,30,31,32,38,39,40)

 

Comment 4: First paragraph on page 3, after Figure 1, line 4: ... of these channels, write "... of these contributions"

Reply: We have rewritten this part according to the reviewer’s suggestion.

 

Modify to:

“and the measurement signal is the result of the superposition of these contributions”

 

Comment 5: Do not indent the text after equations when the parameters are being described.

Reply: Thank you for pointing out the error, we have removed the indentation after equations. (row 109,137,153,157,158,168,173,185,217,219,220)

 

Comment 6: First paragraph of Subsection 2.2.2, the validity of the Okumura-Hata model is 150-1500 MHz

Reply: Since in the abstract of the original reference it is mentioned that the model range is 100MHz-1500MHz, and the frequency band studied in this paper is the FM band in VHF, the term 100MHz was previously adopted, and we have revised the range: “150 MHz-1500 MHz”. (row 148)

 

 (HATA, M. (1980). "Empirical Formula for Propagation Loss in Land Mobile Radio Services." IEEE Transactions on Vehicular Technology.)

 

Comment 7: Check equation 4.

Reply: We have rewritten equation 4 to be consistent with the original literature. (Equation (4))

 

Comment 8: Provide references related to the particle swarm algorithm in Section 3.1 and explain the parameters of Table 1, and justify their value.

Reply:

We have added several references and explained the parameters. (references 30,33,34,35)

 

The additions are as follows:

The number of iterations and population size are both correlated with the search space and search time. The typical range of population size is from 10 to 100. A larger population size allows for more exploration but may increase computation time. The inertia weight controls the balance between exploration and exploitation, with typical values ranging from 0.4 to 0.9. A higher value promotes exploration, while a lower value promotes exploitation. The individual learning factor and social learning factor are parameters that control the influence of the particle's personal best position and the global best position, respectively, typical values range from 1 to 2. A higher cognitive weight emphasizes personal experience, while a higher social weight emphasizes the influence of the swarm. The exchange rate represents the probability of crossover occurring between two individuals during reproduction, with typical values ranging from 0.2 to 0.9 [33-34]. A higher crossover rate promotes exploration and genetic diversity. The mutation rate represents the probability of a gene mutation occurring during reproduction, with typical values ranging from 0.01 to 0.2. A higher mutation rate allows for more exploration and prevents premature convergence [35]. The parameter values in tab. 1 are chosen considering the search accuracy and search time.

 

Comment 9: In equation (12), is the radiation pattern of the tx-antenna considered? If not, explain its impact on the results.

Reply:

EIRP (also known as Effective Isotropic Radiated Power), is defined as the product of the power (P) sent out by the antenna of an antenna and the gain (G) of that antenna: EIRP = P*G, it expresses the joint effect of the transmitted power and the antenna gain. The antenna pattern information is implied in it, and how to extract the direction pattern of the transmitting antenna is also a follow-up of the article. On the other hand, we turn the transmit power into propagation loss, and the directional information of the antenna is also implied in the propagation loss.

 

Comment 10: In Subsection 4.1, the authors indicate that the local received signal needs to be in the range of 20-40 \lambda. If the authors are referring to the small-local fading, the stationary of the channel also depends on the defree of heterogeneity of the environment, and the range may be wider. Please, explain this in the manuscript.

Reply:

Since this paper only considers the model at the level of large-scale path loss, we go to the average value in the range of 20-40 wavelengths in order to filter the small-local fading which is the counterpart of fast fading caused by the movement of the receiver, according to some research on the correlation distance for fast fading this wavelength range is chosen.

 

A.M.D. Turkmani et al. An experimental evaluation of the performance of two-branch space and polarization diversity schemes at 1800 MHz. IEEE Transactions on Vehicular Technology, Volume: 44, Issue 2, pp.318-326, 1995.

 

And it is explained in the lines 277-280.

 

Comment 11: In Figure 4 the map of the terrain must be appear as a primary layer. 

Reply:

We have added the map as the main layer.

 

Modify Figure 4 to:

 

Comment 12: Check first column of Table 6.

Reply:

We changed the first column of the table in detail.

(change the “Determined Model” to “Deterministic Model”, the “Egli” to “Egli Model”, the “Hata” to “Okumura-Hata Model”) (Now is Table 4).

 

Comment 13: Figure 7 better the distance in log-scale, showing the linear relation between the path loss (in dB) and the distance. Write correctly the x and y labels: Loss (dB) instead of Loss/dB.

Reply:

We have replaced Figure 5 and Figure 7 with log-scale.

We have corrected the labels of the figures. (Figure 5, Figure 6, Figure 7)

 

Modify Figure 5 to:

please see the attachment.

Modify Figure 6 to:

please see the attachment.

Modify Figure 7 to:

please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

I am very much satisfied with the answer. The title is now very interesting. I accept the paper in the present form.

Author Response

Dear reviewer,

 

Thank you for your suggestions and constructive comments on our manuscript. We also made some formatting changes based on suggestions from other reviewers. Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

The authors have corrected all the comments made earlier. The article can be accepted for publication.

Author Response

Dear reviewer,

 

Thank you for your suggestions and constructive comments on our manuscript. We also made some formatting changes based on suggestions from other reviewers. Please see the attachment.

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

The authors have implemented the proposed changes and modifications in a satisfactory manner. However, the following corrections are necessary:

1. Write meters in Figure 12 instead longitude and latitude.

2. Use capital letters in the labels (x and y) in all figures.

Author Response

Please see the attachment

Author Response File: Author Response.docx