High-fidelity air-sea cross-domain cluster network full-link channel modeling method

Abstract

The invention relates to the technical field of communication, discloses a full-link channel modeling method for a high-fidelity air-sea cross-domain cluster network, and aims to solve the problem of stagnation of an air-sea cross-domain communication network simulation technology. Through a full-link channel modeling technology, influence factors of a radio channel and an underwater acoustic channel are considered, including relative distance, communication frequency, propagation loss, sea surface temperature and diffusion coefficient in the radio channel, and macroscopic multipath, microscopic multipath and Doppler frequency shift in the underwater acoustic channel. According to the method, related parameters are input, a Jakes model and Bellhop software are used for channel modeling, and finally channel impulse response is obtained through IFFT, so that the reliability and stability of a communication system in a complex environment are improved.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a full-link channel modeling method for a high-vacuum sea cross-domain cluster network. Background Art

[0002] When unmanned equipment systems are interconnected, the transmission medium mutates, and the traditional single wireless communication channel model cannot be applied to cross-domain communication network simulation. By analyzing the influencing factors such as unevenly distributed heterogeneous multi-source link delay, multipath effect, channel interference, etc., the air-sea cross-domain communication channel is simulated, breaking through the high-fidelity modeling of multi-source hybrid channels for air-sea cross-domain communication, evaluating the influencing factors of the cross-domain communication network, and solving the problems of strong test constraints and low resource utilization in actual marine environments.

[0003] Manned / unmanned cross-domain networks are different from traditional wireless communication networks, mainly reflected in the difference in transmission media. Information must not only be transmitted in air channels, but also in underwater channels. This brings many problems to the network that traditional networks do not involve, such as cross-media routing, multi-path interference, channel switching, etc. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides a full-link channel modeling method for a high-vacuum sea cross-domain cluster network. By simulating the real air-sea cross-domain communication environment, it is necessary to study and model the environmental characteristics of the air-sea cross-domain communication channel. The model can calculate the channel environment parameters related to the air-sea cross-domain communication protocol according to the environmental parameters, and intuitively observe the channel impulse response under the underwater acoustic channel.

[0005] The high-vacuum sea cross-domain cluster network full-link channel modeling method provided by the present invention comprises the following steps:

[0006] S1. In the radio channel, input the radio channel parameters, including the transmission signal frequency, propagation distance, and communication frequency, calculate the propagation loss of the radio in the atmosphere according to the Jakes model, and obtain the correlation between the SNR and the change of the communication distance according to the propagation loss, sea surface temperature, diffusion coefficient and other parameters;

[0007] S2. Input the underwater acoustic channel parameters in the underwater acoustic channel, combine the large-scale fading parameters and the small-scale fading parameters to generate the .prm file, input the Doppler parameters to generate the .dop file, and use them together as the input file of Bellhop. Generate the .arr file through Bellhop, and effectively read the .arr file. By screening the multi-cluster paths and combining the small-scale fading coefficients of the micro-paths and superimposing the Doppler effect, the channel gain matrix hmat is finally obtained. After IFFT transformation, the channel impulse response of the underwater acoustic channel that can be intuitively observed is obtained to evaluate the performance of the communication system.

[0008] Preferably, the calculation formula for radio propagation loss in the atmosphere is:

[0009]

[0010] Where n is the path loss exponent (PLE), which is an empirical value obtained by fitting a large amount of experimental data; is shadow fading, which is a zero-mean Gaussian random variable in the decibel domain with a standard deviation of σ, PL FS (f,1m) is the free space path loss (FSPL) at a reference distance of 1m and frequency f.

[0011] Preferably, the calculation formula of the free space path loss (FSPL) is as follows:

[0012]

[0013] Where c is the speed of light, which is 3×10 8 m / s.

[0014] Preferably, the underwater acoustic channel parameters include:

[0015] The path gain and path delay of the sound line reaching the receiving end affected by the macroscopic multipath;

[0016] Each cluster of sound rays arriving at the receiving end is affected by the microscopic multipath of the sound rays;

[0017] Doppler frequency shift caused by autonomous or non-autonomous transmission and water surface fluctuations at both ends of the transmitter and receiver.

[0018] Preferably, the total transfer function in the underwater acoustic time-invariant channel is:

[0019]

[0020] The total system function is represented by N p The fundamental characteristic sound line path, each of which has its own path gain Path delay in Refers to the standard reference system function under path p = 0, path gain Path delay It can be obtained through the .arr file generated by Bellhop.

[0021] Preferably, the steps of underwater acoustic channel modeling based on large-scale fading are as follows:

[0022] a1. Input channel parameters and large-scale fading parameters to generate .prm file;

[0023] a2. Read data, simulate the underwater acoustic channel through Bellhop, and generate .arr file;

[0024] a3. Ignore signals with amplitudes less than the threshold and obtain the channel gain matrix hmat;

[0025] a4. After IFFT transformation, the channel impulse response and channel gain data of the underwater acoustic channel are obtained.

[0026] Preferably, the steps of underwater acoustic channel modeling based on small-scale fading and Doppler shift are as follows:

[0027] b1. Input channel parameters, large-scale parameters, and small-scale parameters to generate a .prm file;

[0028] b2. Use Bellhop to simulate the underwater acoustic channel and generate an .arr file;

[0029] b3. Multi-cluster path screening establishes a small-scale model, combines the small-scale fading coefficient of the micro-path and superimposes the Doppler effect to obtain the channel gain matrix hmat;

[0030] b4. After IFFT transformation, the channel impulse response and channel gain matrix data of the underwater acoustic channel are obtained.

[0031] Compared with the related art, the high-vacuum sea cross-domain cluster network full-link channel modeling method provided by the present invention has the following beneficial effects:

[0032] (1) The present invention improves the cross-domain collaborative capability of underwater AUVs: by loading a cross-domain communication model, the cross-domain communication system adapted to the underwater AUV realizes the information relay function of the distributed networking and the airspace multi-source communication network, and enhances the marine data transmission capability of the underwater AUV, thereby improving its capability;

[0033] (2) The present invention provides theoretical support and prediction for the results of sea trial experiments: through the full-link channel modeling technology of the high-vacuum sea cross-domain cluster network, the sea trial experiment can not only obtain more accurate and reliable experimental results, but also improve the overall efficiency and quality of the experiment with the help of theoretical support and prediction capabilities;

[0034] (3) The present invention enhances the reliability of the communication system: by accurately modeling the channel characteristics, the reliability and stability of the communication system in complex environments are significantly improved, providing data support for the design of efficient and anti-interference communication systems, and optimizing the overall performance of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A schematic diagram of the structure of a full-link channel modeling method for a high-vacuum sea cross-domain cluster network provided by the present invention;

[0036] Figure 2 It is a schematic diagram of the large-scale fading phenomenon in the present invention;

[0037] Figure 3 A flow chart for modeling an underwater acoustic channel based on large-scale fading in the present invention;

[0038] Figure 4 It is a schematic diagram of the small-scale fading phenomenon in the present invention;

[0039] Figure 5 The present invention provides a flow chart for modeling underwater acoustic channels based on small-scale fading and Doppler shift. DETAILED DESCRIPTION

[0040] First of all, it should be noted that due to the lack of research on the characteristics of air-sea cross-domain communication channels and the research on the factors affecting the network under mission conditions, the simulation technology of air-sea cross-domain communication networks is stagnant and urgently needs to be improved. In view of the above problems, full-link channel modeling of radio channels and underwater acoustic channels is considered. The main factors considered in the modeling process are:

[0041] Radio Channels:

[0042] ① The relative distance and communication frequency between the surface node and the aerial node;

[0043] ② Air propagation loss, sea surface temperature, and diffusion coefficient.

[0044] Hydroacoustic channel:

[0045] ① The path gain and path delay of the sound line reaching the receiving end due to the influence of macroscopic multipath;

[0046] ② Each cluster of sound rays arriving at the receiving end is affected by the microscopic multipath of the sound rays;

[0047] ③ Doppler frequency shift caused by autonomous or non-autonomous conditions at both ends of the transmitter and receiver and water surface fluctuations.

[0048] It is known that the total transfer function in the underwater acoustic time-invariant channel is:

[0049]

[0050] The total system function is represented by N p The fundamental characteristic sound line path, each of which has its own path gain Path delay in Refers to the standard reference system function for path p = 0. Path gain Path delay It can be obtained through the .arr file generated by Bellhop.

[0051] The present invention will be further described below in conjunction with the accompanying drawings and implementation modes.

[0052] The embodiment of the present invention provides a high-vacuum cross-domain cluster network full-link channel modeling technology to meet the needs of cross-domain communication. The entire flow chart is as follows: Figure 1 shown, including:

[0053] 1. Radio channel:

[0054] Input the transmission signal frequency, propagation distance, and communication frequency, and calculate the propagation loss of radio in the atmosphere according to the Jakes model. The formula is:

[0055]

[0056] Where n is the path loss exponent (PLE), which is an empirical value obtained by fitting a large amount of experimental data; is shadow fading, which is a zero-mean Gaussian random variable in the decibel domain with a standard deviation of σ, PL FS (f,1m) is the free space path loss (FSPL) at a reference distance of 1m and a frequency of f. The FSPL is calculated as follows:

[0057]

[0058] Where c is the speed of light, which is 3×10 8 m / s.

[0059] 2. Hydroacoustic channel:

[0060] Macroscopic multipath of sound rays:

[0061] Affected by factors such as changes in sea surface height (such as tides) and seabed morphology (undersea earthquakes caused by submarine volcanic activity), the locations of the information source and destination are uncertain, resulting in significant differences in the actual path gain and delay from the values ​​under the standard path. Figure 2 As shown, the deviation caused by this factor is called large-scale fading.

[0062] Large-scale fading changes cause the path length to deviate from the standard path, that is, The change Δl p is considered as a randomly varying value. During the analysis, p Modeled as a function of mean The variance is The delay of the path can be calculated by the path length. p Alternative p The actual path gain can be obtained:

[0063]

[0064] In actual situation Then we can get the following approximate expression:

[0065]

[0066] Combining (2) and (3), we can get:

[0067]

[0068] Now we can get the transfer function of the overall channel under large-scale fading:

[0069]

[0070] The channel impulse response function in the time domain is:

[0071]

[0072] In summary, the steps of underwater acoustic channel modeling based on large-scale fading are as follows: Figure 3 As shown, the following steps are included:

[0073] a1. Input channel parameters and large-scale fading parameters to generate .prm file;

[0074] a2. Read data, simulate the underwater acoustic channel through Bellhop, and generate .arr file;

[0075] a3. Ignore signals with amplitudes less than the threshold and obtain the channel gain matrix hmat;

[0076] a4. After IFFT transformation, the channel impulse response and channel gain data of the underwater acoustic channel are obtained.

[0077] Microscopic multipath of sound rays:

[0078] On the basis of large-scale fading, the scattering phenomenon of intrinsic sound rays is further considered. Various impurities and bubbles in the sea environment will cause each intrinsic sound ray to change from the original one to a cluster of paths surrounding the original sound ray during the propagation process. In addition, the changes caused by local motion (transmitter / receiver drift, water surface fluctuations, etc.) are collectively called small-scale fading, such as Figure 4 shown.

[0079] In order to simulate the underwater acoustic channel more realistically, this paper focuses on the sound rays that are clustered due to scattering of the original single eigenwave. Based on the above, we have given the eigenwave a path gain h p and path delay τ p , due to the influence of scattering, equation (5) will become:

[0080]

[0081] where h p,i , τp,i =τ p +δτ p,i are micropath gain and micropath delay respectively. Considering the uneven distribution of impurities and bubbles in the marine environment, h is set p,i The mean is 0 and the variance is The variable δτ p,i The variance is 0 if the mean is variables, where Can be set manually in the environment configuration. It can be obtained by the following formula:

[0082]

[0083] c is the speed of sound propagation in the underwater acoustic channel, θ p is the incident angle of the pth eigenvalue, n sp is the number of reflections of the pth sound ray from the sea surface, n bp is the number of reflections of the pth sound line and the seabed, both of which can be read from the .arr file of Bellhop. is the variance of sea surface height change, is the variance of seabed height change, both of which can be set artificially in the environmental configuration.

[0084] The small-scale fading factor is artificially set as:

[0085]

[0086] Therefore, the system function of the time-varying underwater acoustic channel based on large-scale and small-scale fading can be obtained as:

[0087]

[0088] The motion of the transmitter, receiver or any reflection point in the channel will cause time-varying path delay. Based on small-scale fading, we are concerned about the changes in a short period of time, so we can reasonably assume that the speed of movement remains constant during this time interval. At this time, we consider introducing the deterministic Doppler a caused by the relative uniform motion of the two ends of the transmitter and receiver. p , random Doppler δa p,i The mean is 0 and the variance is It can be set manually in the environment configuration, where the deterministic Doppler satisfies the following formula:

[0089]

[0090] Based on the introduced Doppler frequency shift, the small-scale fading factor can be rewritten as:

[0091]

[0092] The Doppler factor in the above formula is the sum of the deterministic Doppler and the random Doppler.

[0093] In summary, the steps of underwater acoustic channel modeling based on small-scale fading and Doppler frequency shift are as follows: Figure 5 As shown, the following steps are included:

[0094] b1. Input channel parameters, large-scale parameters, and small-scale parameters to generate a .prm file;

[0095] b2. Use Bellhop to simulate the underwater acoustic channel and generate an .arr file;

[0096] b3. Multi-cluster path screening establishes a small-scale model, combines the small-scale fading coefficient of the micro-path and superimposes the Doppler effect to obtain the channel gain matrix hmat;

[0097] b4. After IFFT transformation, the channel impulse response and channel gain matrix data of the underwater acoustic channel are obtained.

[0098] Therefore, the whole process of underwater acoustic time-varying channel modeling is shown in the following table:

[0099]

[0100]

[0101] Compared with the related art, the high-vacuum sea cross-domain cluster network full-link channel modeling method provided by the present invention has the following beneficial effects:

[0102] The present invention provides a full-link channel modeling method for a high-vacuum sea cross-domain cluster network, which improves the cross-domain collaboration capability of underwater AUVs, provides theoretical support and prediction for sea trials, and enhances the reliability of the communication system.

[0103] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A full-link channel modeling method for a high-vacuum sea cross-domain cluster network, characterized in that: The following steps are involved: S1. In the radio channel, input the radio channel parameters, including the transmission signal frequency, propagation distance, and communication frequency, calculate the propagation loss of the radio in the atmosphere according to the Jakes model, and obtain the correlation between the SNR and the change of the communication distance according to the propagation loss, sea surface temperature, diffusion coefficient and other parameters; S2. Input the underwater acoustic channel parameters in the underwater acoustic channel, combine the large-scale fading parameters and the small-scale fading parameters to generate the .prm file, input the Doppler parameters to generate the .dop file, and use them together as the input file of Bellhop. Generate the .arr file through Bellhop, and effectively read the .arr file. By screening the multi-cluster paths and combining the small-scale fading coefficients of the micro-paths and superimposing the Doppler effect, we finally get the channel gain matrix hmat, and then after IFFT transformation, we get the channel impulse response of the underwater acoustic channel that can be visually observed to evaluate the performance of the communication system.

2. The high-vacuum sea cross-domain cluster network full-link channel modeling method according to claim 1 is characterized in that: The formula for calculating radio propagation loss in the atmosphere is: Where n is the path loss exponent (PLE), which is an empirical value obtained by fitting a large amount of experimental data; is shadow fading, which is a zero-mean Gaussian random variable in the decibel domain with a standard deviation of σ, PL FS (f,1m) is the free space path loss (FSPL) at a reference distance of 1m and frequency f.

3. The high-vacuum sea cross-domain cluster network full-link channel modeling method according to claim 2 is characterized in that: The calculation formula of the free space path loss (FSPL) is as follows: Where c is the speed of light, which is 3×10 8 m / s.

4. The high-vacuum sea cross-domain cluster network full-link channel modeling method according to claim 1 is characterized in that: The underwater acoustic channel parameters include: The path gain and path delay of the sound line reaching the receiving end affected by the macroscopic multipath; Each cluster of sound rays arriving at the receiving end is affected by the microscopic multipath of the sound rays; Doppler frequency shift caused by autonomous or non-autonomous transmission and water surface fluctuations at both ends of the transmitter and receiver.

5. The high-vacuum sea cross-domain cluster network full-link channel modeling method according to claim 1 is characterized in that: The total transfer function under the underwater acoustic time-invariant channel is: The total system function is represented by N p The fundamental characteristic sound line path, each of which has its own path gain Path delay in Refers to the standard reference system function under path p = 0, path gain Path delay It can be obtained through the .arr file generated by Bellhop.

6. The high-vacuum sea cross-domain cluster network full-link channel modeling method according to claim 1 is characterized in that: The steps of underwater acoustic channel modeling based on large-scale fading are as follows: a1. Input channel parameters and large-scale fading parameters to generate .prm file; a2. Read data, simulate the underwater acoustic channel through Bellhop, and generate .arr file; a3. Ignore signals with amplitudes less than the threshold and obtain the channel gain matrix hmat; a4. After IFFT transformation, the channel impulse response and channel gain data of the underwater acoustic channel are obtained.

7. The high-vacuum sea cross-domain cluster network full-link channel modeling method according to claim 1 is characterized in that: The steps of underwater acoustic channel modeling based on small-scale fading and Doppler shift are as follows: b1. Input channel parameters, large-scale parameters, and small-scale parameters to generate a .prm file; b2. Use Bellhop to simulate the underwater acoustic channel and generate an .arr file; b3. Multi-cluster path screening establishes a small-scale model, combines the small-scale fading coefficient of the micro-path and superimposes the Doppler effect to obtain the channel gain matrix hmat; b4. After IFFT transformation, the channel impulse response and channel gain matrix data of the underwater acoustic channel are obtained.

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