Research on Indoor Multi-Scene Base Station Deployment Method Based on HDOP

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Dear Author:

I have thoroughly read your submitted manuscript and I am intrigued by the research you have conducted. In the following sections, I will provide detailed suggestions to help enhance your research further.

 

1.      The paper lacks both theory and innovation. To improve HDOP in different scenarios, a specific station layout model or method should be proposed instead of directly calculating HDOP based on several layout styles to draw layout conclusions.

2.      The paper only discusses the layout methods of two ideal scenarios, circular and rectangular, which are easily thought of by peers or obtained through simulation. The author should consider layout schemes under irregular shapes or occlusions to be genuinely innovative or attractive to readers.

3.      Although much practical work has been done in this paper, the significance of building an experimental platform to verify the relationship between HDOP and positioning error is insignificant, as their relationship is already well-known.

 

Based on the above considerations, I hope you can revise the paper carefully. Thank you once again for submitting to us.

 

Thank you!

Sincerely,

Reviewer

Comments for author File: Comments.pdf

Author Response

Response to reviewer 1:

Dear reviewer, thank you very much for taking the time to review our paper amidst your busy schedule. We have made revisions to the paper according to your feedback, which has greatly enhanced our work. We will now respond to each of your comments one by one.

1. The paper lacks both theory and innovation. To improve HDOP in different scenarios, a specific station layout model or method should be proposed instead of directly calculating HDOP based on several layout styles to draw layout conclusions.

Reply: Thank you very much for providing this suggestion, it makes this article more complete.

In response to your first point that this article lacks theoretical description and innovation, our team is focused on practical engineering applications and has been committed to the research and application of indoor positioning technologies such as UWB and 5G for many years. Our starting point is to complete actual project engineering, so the innovation points of this article may not be sufficient, which is also the key direction we need to strive for in theoretical innovation in the future. The biggest contribution of this article in terms of theory is the provision of the theoretical minimum value of HDOP corresponding to different numbers of base stations, and based on this, the recommended number of base stations for practical engineering is given. The reason for writing this article is that we have observed that there are currently few experimental studies to verify the relationship between HDOP and positioning error. Although theoretically, a smaller HDOP means a smaller positioning error, indoor scenes are complex. Considering the complexity of indoor scenes, such as walls and large furniture, which can seriously affect the propagation of positioning signals and the deployment of base stations, this article still conducted experiments to verify the relationship between HDOP and positioning error in practical engineering, achieving a closed loop between theory and experiment.

Regarding your second point, this is an oversight in our description. In fact, the final optimal layout method in this article was calculated by the particle swarm optimization algorithm. The other layout methods used for comparison were obtained by consulting literature and observing the calculation formula of HDOP. After comparing these layout methods, it was found that the layout method obtained by the particle swarm optimization algorithm was indeed the smallest HDOP, which verified the feasibility of the particle swarm optimization algorithm in this regard. Therefore, it can be considered that the base station layout method ultimately selected in this article is the smallest HDOP layout method. At present, we have provided supplementary explanations on this aspect in the paper, and the supplementary content has been highlighted in red.     

 

2. The paper only discusses the layout methods of two ideal scenarios, circular and rectangular, which are easily thought of by peers or obtained through simulation. The author should consider layout schemes under irregular shapes or occlusions to be genuinely innovative or attractive to readers.

Reply: Thank you very much for your suggestion. As you mentioned, rectangles and circles are the two most common indoor positioning scenarios and are also the most familiar to readers. We should consider the distribution of base stations in other more special scenarios. We have added the optimal base station distribution method for the "L" - shaped region in the revised manuscript, but due to space limitations, this section only provides the optimal base station distribution method and does not show the comparison process with other station layout methods like the rectangular and circular sections.

 

3. Although much practical work has been done in this paper, the significance of building an experimental platform to verify the relationship between HDOP and positioning error is insignificant, as their relationship is already well-known.

Reply: As you said, theoretically speaking, the relationship between HDOP and positioning error is well known. However, indoor scenes are complex. Considering the complexity of indoor scenes, such as walls, large furniture, and other factors that can seriously affect the propagation of positioning signals and the deployment of base stations, this article still conducted experiments to verify the relationship between HDOP and positioning error in practical engineering, aiming to achieve a closed loop between theory and experiment, and provide strong reference for the deployment of base stations in practical engineering. Measured data show that the positioning error is roughly proportional to HDOP, but there are exceptions, and this article analyzes the possible causes.

Thank you again for taking the time out of your busy schedule to review our paper. Your feedback has made our paper more complete. It can be seen that you are an expert in indoor positioning and have extensive knowledge. We have revised the paper according to your feedback and responded to each one. If our ideas and descriptions are incorrect, we hope you can point them out. We really hope to learn from you. Finally, I wish you a happy life and smooth work.

Reviewer 2 Report

Comments and Suggestions for Authors

The paper analyzes HDOP in indoor positioning across multiple scenarios, and proposes optimal base station deployment strategies for circular and rectangular environments. In general the paper is in good shape and the presentation is clear. However, the reviewer feels that there are still some rooms to improve before possible acceptance of publication.

Here are some weakness:

1) The main criticism is about the novelty of the paper. For example, the theoretical analysis and the difference from the prior works should be given, although a lot of experiments are done in the paper.

2) The experimental platform is limited in scale. The paper should enhance its credibility by including more extensive experimental scenarios or larger datasets.

3) The complexity or runtime efficiency of the proposed algorithm should be given in the paper, which is useful for practical implementation.

4) The comparison of the proposed deployment strategies with other algorithms in the field should be added to complement the experiments. 

Author Response

Reply reviewer 2:

Dear reviewer, thank you very much for taking the time to review our paper amidst your busy schedule. We have made revisions to the paper according to your feedback, which has greatly enhanced our work. We will now respond to each of your comments one by one.

1. The main criticism is about the novelty of the paper. For example, the theoretical analysis and the difference from the prior works should be given, although a lot of experiments are done in the paper.

Reply: In response to your point, our team is focused on practical engineering applications and has been committed to the research and application of indoor positioning technologies such as UWB and 5G for many years. Our starting point is to complete actual project engineering, so the innovation points of this article may not be very sufficient, which is also the key direction we need to strive for in theoretical innovation in the future. The biggest contribution of this article in terms of theory is the provision of the theoretical minimum value of HDOP corresponding to different numbers of base stations, and based on this, the recommended number of base stations for practical engineering is given. The opportunity for writing this article is that we have observed that there are currently few experimental studies to verify the relationship between HDOP and positioning error. Although theoretically, a smaller HDOP means a smaller positioning error, indoor scenes are complex. Considering the complexity of indoor scenes, such as walls and large furniture, which can seriously affect the propagation of positioning signals and the deployment of base stations, this article still conducted experiments to verify the relationship between HDOP and positioning error in practical engineering, achieving a closed loop between theory and experiment. We have added supplementary explanations for this section in the introduction of the first part.

 

2. The experimental platform is limited in scale. The paper should enhance its credibility by including more extensive experimental scenarios or larger datasets.

Reply: Thank you very much for your suggestion. In fact, this is also one of the problems we most want to solve. Due to the lack of attention from scholars on this part of the work, we have not found a publicly available open-source dataset. It is difficult to actually build positioning devices for special scenarios such as circular ones. Therefore, our team currently only has indoor positioning experimental sites for rectangular scenarios. We should improve its credibility by including a wider range of experimental scenarios or larger datasets. This is a limitation of this article, and we have included this issue at the end of the summary section in the revised manuscript, which is one of the directions we aim to work on.

 

3. The complexity or runtime efficiency of the proposed algorithm should be given in the paper, which is useful for practical implementation.

Reply: Thank you very much for providing this suggestion. It was our negligence. In the revised manuscript, we added a description of the time and space complexity of the algorithm in section 3.1. Your suggestion makes our paper more complete.

 

4. The comparison of the proposed deployment strategies with other algorithms in the field should be added to complement the experiments.

Reply: This article mainly presents the minimum base station distribution method for HDOP in circular, rectangular, and L-shaped scenarios, and builds an experimental platform to verify the relationship between HDOP and positioning error in practical engineering using measured data, achieving a closed loop in theory and experiment. Therefore, no comparison with other algorithms is given. At present, our team is also conducting research on algorithm innovation in this area, but unfortunately, our research is still ongoing and may not be able to be added to this paper in time. Thank you very much for your feedback, and this part will appear in our future papers.

Thank you again for taking the time out of your busy schedule to review our paper. Your feedback has made our paper more complete. It can be seen that you are an expert in indoor positioning and have extensive knowledge. We have revised the paper according to your feedback and responded to each one. If our ideas and descriptions are incorrect, we hope you can point them out. We really hope to learn from you. Finally, I wish you a happy life and smooth work.

Reviewer 3 Report

Comments and Suggestions for Authors

This paper provides an analysis of the relationship between anchor deployment and localization accuracy in indoor positioning scenarios. The authors focus specifically on HDOP(Horizontal Dilution of Precision) and provide a relationship to positioning error. This paper presents the HDOP values according to the number of anchors and anchor deployment through theoretical analysis, simulation analysis, and empirical analysis.

I think the issues addressed in this paper are very important. In particular, this paper will be very helpful for researchers of indoor positioning.

Comments

1.     Anchor deployments are highly dependent on physical environment factors such as building structure, walls, and obstacles, making it impossible to install them in theoretical optimal locations. In general, scenarios without deployment constraints, such as rectangular or circular scene presented in the paper, are easy to deploy anchors optimized without this kind of analysis. So I think the authors need to consider environments with limited deployment, such as real-world indoor spaces.

2.     The paper only provides analysis and does not present any solutions. I recommend to propose the anchor deployment strategy through the lessons presented in this paper.

 

3.     I think this paper does not provide enough related works especially about the deployment issue. I introduce a paper that propose an anchor deployment strategy from a practical perspective. (H. Chen and A. Dhekne, "PnPLoc: UWB Based Plug & Play Indoor Localization," 2022 IEEE 12th International Conference on Indoor Positioning and Indoor Navigation (IPIN), Beijing, China, 2022, pp. 1-8, doi: 10.1109/IPIN54987.2022.9918119.) In addition to this paper, further studies on anchor deployment should be introduced and analyses of related studies should be presented.

 

Author Response

Reply reviewer 3:

Dear reviewer, thank you very much for taking the time to review our paper amidst your busy schedule. We have made revisions to the paper according to your feedback, which has greatly enhanced our work. We will now respond to each of your comments one by one.

1. Anchor deployments are highly dependent on physical environment factors such as building structure, walls, and obstacles, making it impossible to install them in theoretical optimal locations. In general, scenarios without deployment constraints, such as rectangular or circular scene presented in the paper, are easy to deploy anchors optimized without this kind of analysis. So, I think the authors need to consider environments with limited deployment, such as real-world indoor spaces.

Reply: Thank you very much for your suggestion. Your viewpoint is very correct. Indoor scenes are complex, and considering the complexity of indoor scenes, such as walls and large furniture, factors can seriously affect the propagation of positioning signals and the deployment of base stations. We did not provide this explanation in the previous version of the paper. In the revised manuscript, we have added the missing content in section 3.3. Combined with the base station distribution method built by our team in reality, it should have some inspiration and reference value for readers.

2. The paper only provides analysis and does not present any solutions. I recommend to propose the anchor deployment strategy through the lessons presented in this paper.

Reply: In the revised manuscript, we provide a base station distribution method for reference and inspiration in practical engineering, that is, when the positioning scene is circular, the minimum HDOP deployment method is to evenly lay base stations along the circumference. In a rectangular scene, the optimal base station deployment plan for 6 base stations is to deploy them at 4 vertices and in the middle of the two long sides. In reality, the deployment height of base stations depends on physical environmental factors such as building structure, walls, and obstacles, which makes it impossible to install them in the theoretically optimal position. Therefore, in the actual deployment of base stations, the optimal distribution of base stations given in this article can be referred to, but adjustments should also be made according to the characteristics of the actual scenario.

3. I think this paper does not provide enough related works especially about the deployment issue. I introduce a paper that propose an anchor deployment strategy from a practical perspective. (H. Chen and A. Dhekne, "PnPLoc: UWB Based Plug & Play Indoor Localization," 2022 IEEE 12th International Conference on Indoor Positioning and Indoor Navigation (IPIN), Beijing, China, 2022, pp. 1-8, doi: 10.1109/IPIN54987.2022.9918119.) In addition to this paper, further studies on anchor deployment should be introduced and analyses of related studies should be presented.

Reply: As you said, we did not provide sufficient introduction to the relevant work, especially regarding deployment issues. The paper you provided has effectively supplemented the deficiencies in this aspect of the article. The quality of this paper is very high and it makes up for the lack of reference citation in this article. Thank you very much.

Thank you again for taking the time out of your busy schedule to review our paper. Your feedback has made our paper more complete. It can be seen that you are an expert in indoor positioning and have extensive knowledge. We have revised the paper according to your feedback and responded to each one. If our ideas and descriptions are incorrect, we hope you can point them out. We really hope to learn from you. Finally, I wish you a happy life and smooth work.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Dear Author:

Thank you for your detailed response. Considering the innovation and completeness of the paper, please add the following content.

 

1.      Please provide the specific process of using the Particle Swarm Optimization (PSO) algorithm for the first layout method and the references and processing details for the second layout method.

2.      The addition of L-shaped scenes is more attractive to readers, but the conclusion is somewhat abrupt. Please provide specific details to prove that Figures 13 and 14 are the optimal layouts. Why not consider placing stations at the corners of the L-shaped or slightly further to the right?

 

Based on the above considerations, I hope you can revise the paper carefully.

 

Thank you!

Sincerely,

Reviewer

Comments for author File: Comments.pdf

Author Response

Reply to Reviewer 1:

Dear reviewer,

Hello!

First of all, thank you very much for taking the time out of your busy schedule to review my paper again and provide constructive feedback. We have made revisions to the paper according to your suggestions and are now responding to your comments one by one.

1. Please provide the specific process of using the Particle Swarm Optimization (PSO) algorithm for the first layout method and the references and processing details for the second layout method.

Reply: Thank you very much for pointing out the issue we have. In the previous version of the paper, our description of this part was too concise and did not fully reflect our thinking and work. In the revised manuscript, we have added approximately 200 words of description in section 3.1: “The first station layout method is obtained through the use of particle swarm optimization (PSO) algorithm. PSO algorithm is an optimization algorithm based on swarm intelligence, proposed by Eberhart and Kennedy in 1995 [16]. It is inspired by the foraging behavior of bird flocks and simulates their social behavior when searching for food. The PSO algorithm has been widely applied in many optimization problems due to its simplicity, ease of implementation, and few parameters. The PSO algorithm requires setting a reasonable fitness function for iteration. In this paper, points are selected according to a certain density within the positioning area, and the average HDOP value of these points is used as the fitness function to find the base station distribution method that minimizes the average HDOP value of each point. The second method is the station layout method obtained by consulting literature and observing the HDOP calculation formula, which may have a smaller HDOP. It is generally believed that the more evenly distributed the base stations are, the more symmetrical they are, and the overall HDOP is smaller. Comparing these two methods aims to find the station layout method with the smallest HDOP in this scenario [17][18].” We believe this will help readers understand our work.

2. The addition of L-shaped scenes is more attractive to readers, but the conclusion is somewhat abrupt. Please provide specific details to prove that Figures 13 and 14 are the optimal layouts. Why not consider placing stations at the corners of the L-shaped or slightly further to the right?

Reply: The conclusion in this section was obtained through PSO algorithm calculation. Regarding the calculation process, we have provided a certain description in this version. The base station distribution shown in Figure 13 and Figure 14 is obtained using PSO optimization algorithm to minimize the overall HDOP average value in the region. Our calculation process should be fine, as the optimal base station distribution obtained by our algorithm in common indoor positioning scenarios such as rectangles and circles are consistent with other literature and practical engineering methods. Therefore, we believe that our algorithm is also applicable in the "L" - shaped region. As for why you suggested not considering setting up base stations at the corners of the L-shape, we have also carefully considered this part of the content. It may be because the short side of the area proposed in this article is too short compared to the long side, and setting up base stations on the right side of the short side does not significantly improve most points. If there are additional base stations that can be set up, we may consider the points you mentioned.

Thank you again for your feedback. We sincerely believe that your suggestions have made our paper completer and more rigorous. It can be seen that you are an expert in the field of indoor positioning, who has conducted in-depth research in this area and has rich professional knowledge. It is a great pleasure to exchange academic content with you, and we have gained a lot from it. Wishing you a happy life and all the best!

Reviewer 2 Report

Comments and Suggestions for Authors

I have no further comments.

Author Response

Thank you again for your feedback. We sincerely believe that your suggestions have made our paper completer and more rigorous. It can be seen that you are an expert in the field of indoor positioning, who has conducted in-depth research in this area and has rich professional knowledge. It is a great pleasure to exchange academic content with you, and we have gained a lot from it. Wishing you a happy life and all the best!

Reviewer 3 Report

Comments and Suggestions for Authors

The revised paper incorporates my comments well. 

This paper is expected to provide theoretical guidelines in practical infrastructure deployment situations.

Author Response

Thank you again for your feedback. We sincerely believe that your suggestions have made our paper completer and more rigorous. It can be seen that you are an expert in the field of indoor positioning, who has conducted in-depth research in this area and has rich professional knowledge. It is a great pleasure to exchange academic content with you, and we have gained a lot from it. Wishing you a happy life and all the best!

Round 3

Reviewer 1 Report

Comments and Suggestions for Authors

Dear Author:

Thank you for your detailed response.  I have accepted and recommended the publication.

Sincerely,

Reviewer