Dual Threshold Cooperative Sensing Based Dynamic Spectrum Sharing Algorithm for Integrated Satellite and Terrestrial System
Round 1
Reviewer 1 Report
In this paper, cognitive radio technology is introduced into the integrated satellite-terrestrial system to dynamically realize spectrum sharing and increase its utilization. The spectrum sensing scenario of the integrated satellite-terrestrial system is studied and the fading situation of the sensing link is determined. The authors introduce the equal-gain combining algorithm to improve the decision making accuracy of the fuzzy state. The simulation results show that the optimal values of the two thresholds vary with SNR, which can dynamically adapt to the complex scene of the satellite-integrated ground system.
The paper is quite interesting, however, some comments on my concerns are left here:
1. The introduction does not address all the most recent state of the art, there are important papers that are being omitted, a deeper literature review should be done, and the contributions part should be rewritten, as it is not very clear about this.
2. To make an exhaustive revision of the grammar.
3. Figures 3-7 should have the axes and labels in larger font size and should be discussed in more depth in the text.
Author Response
一、Reviewer 1：
- The introduction does not address all the most recent state of the art, there are important papers that are being omitted, a deeper literature review should be done, and the contributions part should be rewritten, as it is not very clear about this.
Answer：The introduction has been revised according to the comments of the reviewers, and the latest literature has been supplemented. The contribution section has also been revised as shown below.
In this paper, cognitive radio technology is introduced into the integrated satellite terrestrial system to dynamically realize spectrum sharing to increase spectrum utiliza-tion. The spectrum sensing scenario of the integrated satellite terrestrial system is studied, and the fading situation of the sensing link is determined. However, the uncertainty of noise interference in the system can lead to a fuzzy state of perception. The traditional double-threshold cooperative sensing technology usually ignores the detected fuzzy state. Therefore, the equal-gain combination algorithm is introduced to improve the decision-making accuracy of the fuzzy state. Furthermore, the optimal value of voting thresh-old and dual threshold algorithm is derived based on the equal gain combination algorithm to minimize the error probability. The simulation results show that the optimal values of the two thresholds vary with the SNR, which can dynamically adapt to the complex scene of the integrated satellite terrestrial system. The dual-threshold cooperative spectrum sharing algorithm improves the detection accuracy of the integrated satellite terrestrial sensing system. Cognitive technology increases the opportunity for ground systems to share satellite spectrum, reduces the interference of ground systems to satellite systems, and alleviates the current shortage of spectrum resources.
- To make an exhaustive revision of the grammar.
Answer：According to the opinions of reviewers, the content of the article has been polished.
- Figures 3-7 should have the axes and labels in larger font size and should be discussed in more depth in the text.
Answer：Axes and labels for Figures 3–7 have been used in larger font and are discussed in more depth in the text.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
In order to improve the detection performance, a double threshold cooperation energy detection algorithm for the satellite-based integrated system based on voting optimization was established, and the formula of the adaptive double threshold energy detection cooperation was derived. The accuracy of the detection algorithm was verified by simulation.
But the following comments should be considered:
1. I recommend to check the presentation of the paper. The writing style could be improved. Please check carefully the form, the grammar and the construction of the phrases.
2.The literature could be updated with new related works.
3. The shared frequency band is S band in the paper, why not Ka or even Q or V band? Ka band is now widely used in satellite communication systems, such as Starlink or Oneweb system.
4. The paper did not indicate what kind of satellite，GEO satellite or LEO satellite?
5. In the section of simulation results and analysis, the paper says “Figure 3 and Figure 4 are the curves of the detection probability of the satellite terrestrial integrated system with the change of the SNR in the case of different noise uncertainties of the dual-threshold cooperative energy detection technology”. Why the ordinates of figures 3 and 4 are the error probability instead of the detection?
Author Response
二、Reviewer 2：
- I recommend to check the presentation of the paper. The writing style could be improved. Please check carefully the form, the grammar and the construction of the phrases.
Answer：According to the opinions of reviewers, the content of the article has been polished.
- The literature could be updated with new related works.
Answer：The introduction has been revised according to the comments of the reviewers, and the latest literature has been supplemented. The contribution section has also been revised as shown below.
- The shared frequency band is S band in the paper, why not Ka or even Q or V band? Ka band is now widely used in satellite communication systems, such as Starlink or Oneweb system.
Answer：Since the current s-band frequency is quite scarce, it has been used by terrestrial and satellite networks. Moreover, the focus of this paper is on spectrum sensing technology. The frequency will not have a significant impact on the results of spectrum sensing, so the s-band is used for simulation research.
- The paper did not indicate what kind of satellite，GEO satellite or LEO satellite?
Answer：This article has been revised based on the comments of the reviewers. Due to the use of the s-band, and this frequency band is currently used by GEO satellites and ground networks. Therefore, GEO satellites are used in this paper.
- In the section of simulation results and analysis, the paper says “Figure 3 and Figure 4 are the curves of the detection probability of the satellite terrestrial integrated system with the change of the SNR in the case of different noise uncertainties of the dual-threshold cooperative energy detection technology”. Why the ordinates of figures 3 and 4 are the error probability instead of the detection?
Answer：Thanks to the comments of the reviewers, the error probabilityis correct in the text. Moreover, a lower error probability means a stronger detection capability of the spectrum sensing system.
Author Response File: Author Response.pdf
Reviewer 3 Report
Cognitive radio is introduced into the integrated satellite and terrestrial system to realize spectrum sharing in dynamic spectrum environment. To solve the problem of low signal-to-noise ratio and noise uncertainty in the system, the double threshold cooperative perception strategy is proposed. Different from the traditional adaptive double threshold cooperative perception, the equal-gain merging algorithm is introduced in the fuzzy region to improve the decision accuracy. Simulation results verify the effectiveness of the proposed algorithm.
Even though, there are some suggestions to the paper:
1.The paper sometimes uses integrated satellite and terrestrial system and sometimes uses satellite-terrestrial integrated system, satellite terrestrial integrated system, these three phases should be unify in the paper.
2.The paper should explain why the noise uncertainty and fuzzy state will appear in the integrated satellite and terrestrial system?
3.There is a lot of formula derivation in the paper. Each variable should be defined accordingly.
4.The ordinates of figures 3 and 4 should be the detection probability instead the error probability. Please confirm it.
5. How to model the channel of the integrated satellite and terrestrial system? Please explain Rice factor K=5dB?
6.The paper should supplement the implementation complexity analysis of the proposed spectrum sensing algorithm.
Author Response
三、Reviewer 3：
- The paper sometimes uses integrated satellite and terrestrial system and sometimes uses satellite-terrestrial integrated system, satellite terrestrial integrated system, these three phases should be unify in the paper.
Answer：Thanks to the reviewers for their opinions, the text has been uniformly corrected to be a integrated satellite terrestrial system.
- The paper should explain why the noise uncertainty and fuzzy state will appear in the integrated satellite and terrestrial system?
Answer：1. Traditional energy detection generally assumes that the noise power is definite. However, there is Gaussian white noise and other interferences in the satellite-ground integrated cognitive system. Moreover, noise power changes with time and relative position within a certain range, and the instability of this noise is noise uncertainty. The sensing system will deteriorate the spectrum sensing performance due to the increase of noise uncertainty.
- According to Figure 2, when the energy detected by the system is between the dual thresholds , it is difficult for the perception system to judge whether it is an authorized user or noise, thus creating an fuzzy state.
Figure 2. Energy distribution of noise and signal
- There is a lot of formula derivation in the paper. Each variable should be defined accordingly.
Answer：According to the opinion of the reviewers, the variables in the formula have been defined.
- The ordinates of figures 3 and 4 should be the detection probability instead the error probability. Please confirm it.
Answer：Thanks to the comments of the reviewers, the error probabilityis correct in the text. Moreover, a lower error probability means a stronger detection capability of the spectrum sensing system.
- How to model the channel of the integrated satellite and terrestrial system? Please explain Rice factor K=5dB?
Answer：Thanks to the reviewers for their opinions, the satellite-terrestrial channel in this paper uses the Rice channel, and the Rice factor is a variable in the Rice channel model. Moreover, the intensity of channel fading can be simulated by changing the size of the Rice factor. The Rice factor K=5dB describes the channel situation of medium fading intensity.
- The paper should supplement the implementation complexity analysis of the proposed spectrum sensing algorithm.
Answer: The error probability considered in this paper is related to the perceived channel energy, and it is not easy to analyze the complexity. However, the simulation results show that the system can detect information in a timely and effective manner, thereby improving the spectrum utilization of the system.
Author Response File: Author Response.pdf
Reviewer 4 Report
Considering the influence of noise uncertainty and low signal-to-noise ratio in the channel in integrated satellite terrestrial system, this manuscript proposes a dual-threshold cooperative sensing strategy, which improves the decision-making accuracy, so that the idle spectrum resources can be better utilized. This is of great significance for improving the spectral efficiency of the integrated satellite terrestrial system. However, this manuscript has the following problems to be improved.
1. Some formula variables are not explained, and the variables in different formulas are not uniform. For example, ri is defined as a vector in formula (2), sigma in formula (3) is not defined, and the threshold lamda1, lamda2 in formula (9) contradicts with lamda0, lamda1 in formula (17), etc.
2. The manuscript states that when the noise power is unknown, the threshold value can be calculated by formula (5). However, the calculation of formula (5) requires the value of noise power, the author should check whether the description conflicts with the formula representation. The same problem happens between the descriptions of interfering links of figure 1 with what actually shows.
3. The conclusions of some formulas should be deduced or cited, such as formulas (7), (8) and (22); in addition, the correctness of some derivations should also be checked carefully.
4、In the conclusion analysis, the physical meaning of the ordinate of some figures is wrong, and there are errors in the description and citation of the figure needed to be corrected, such as "Figure 5-4" and so on.
Author Response
四、Reviewer 4：
- Some formula variables are not explained, and the variables in different formulas are not uniform. For example, ri is defined as a vector in formula (2), sigma in formula (3) is not defined, and the threshold lamda1, lamda2 in formula (9) contradicts with lamda0, lamda1 in formula (17), etc.
Answer：Thanks to the comments of the reviewers, the variables of the formula in the text have been defined.
In formula (2), ri is the i-th sensed signal energy, Ri is the detection statistics.
In formula (3),σ2 is the noise power.
In formula (9), the dual threshold of spectrum sensing technology adopts lambda1 and lambda2.
In formula (17), the dual threshold of spectrum sensing technology adopts lambda0 and lambda1.
- The manuscript states that when the noise power is unknown, the threshold value can be calculated by formula (5). However, the calculation of formula (5) requires the value of noise power, the author should check whether the description conflicts with the formula representation. The same problem happens between the descriptions of interfering links of figure 1 with what actually shows.
Answer：Thanks to the reviewers for their comments, the calculation of Equation (5) requires known noise power σ2. The drawing of the interfering link in Figure 1 has been corrected.
- The conclusions of some formulas should be deduced or cited, such as formulas (7), (8) and (22); in addition, the correctness of some derivations should also be checked carefully.
Answer：Thanks to the reviewers for their comments, formulas (7), (8) can be obtained by the derivation of the detection probability and false alarm probability formulas. The correctness of the formula derivation has been carefully checked.
- In the conclusion analysis, the physical meaning of the ordinate of some figures is wrong, and there are errors in the description and citation of the figure needed to be corrected, such as "Figure 5-4" and so on.
Answer：Thanks to the reviewers for their comments. The ordinate in the simulation results is the error probability, and the error probability is the probability of system detection failure. Moreover, a lower error probability means a stronger detection capability of the spectrum sensing system. References and descriptions in the text have been modified.
Author Response File: Author Response.pdf
