Turbulence model for underwater wireless optical communication and communication system performance calculation method

Abstract

The invention discloses a turbulence model for underwater wireless optical communication and a communication system performance calculation method, and the method comprises the steps: building a new turbulence statistical distribution model under the condition of ocean turbulence, and obtaining an expression of a flicker index of the model in combination with model parameters; and a Meijer-G function and a Fox-H function are utilized to obtain a closed expression of the outage probability and the bit error rate under the model condition, so that the influence on the transmission performance of the system under different scene parameters can be researched. Compared with an existing turbulence model, the method is closer to the complex turbulence environment of the ocean, and especially under the complex turbulence scene of bimodal distribution, simulation research on the real ocean environment can be better achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless optical communication, and in particular relates to a turbulence model of underwater wireless optical communication and a method for calculating the performance of a communication system. Background Art

[0002] Common underwater wireless communication methods mainly include underwater acoustic communication, underwater radio electromagnetic wave communication and underwater wireless optical communication (UWOC). Underwater radio electromagnetic wave communication requires a large antenna size and transmission power, so it is not easy to miniaturize the equipment, and it is only applicable to short-distance and low-bandwidth scenarios. In contrast, underwater acoustic communication technology is more mature and has a wider range of applications. Since the attenuation of sound waves in seawater is extremely low, about 2 to 3 decibels per kilometer, under low-frequency conditions, sound waves can even propagate hundreds of kilometers in the ocean, which gives underwater acoustic communication the advantages of long-distance transmission and high reliability. However, underwater acoustic communication also has its limitations, such as large communication delays, bandwidth limitations, high energy consumption and large equipment volume, and serious multipath effects due to reflections from the water surface and the seabed. With the advancement of underwater detection technology, the demand for underwater wireless communication technology is also increasing, especially the increasing demand for low-power and high-bandwidth systems, which are difficult to fully meet by underwater acoustic communication. On the other hand, underwater wireless optical communication, with its powerful information carrying capacity, small communication delay, large bandwidth and good confidentiality, shows great potential in marine resource development and marine environment monitoring. Therefore, promoting the research and development of UWOC technology is not only a key link in building a strong maritime nation, but also has important significance for promoting the rapid development of my country's marine information technology.

[0003] Seawater contains a variety of complex substances, which makes the propagation of wireless light in seawater face multiple challenges, including absorption, scattering and significant turbulence effects. Figure 1 As shown. The absorption effect in seawater will cause the energy of the optical signal to gradually be lost during the propagation process, while the scattering effect will change the original propagation direction of the optical signal and cause the signal to deviate. The turbulence effect in seawater, due to the influence of temperature, salinity and bubbles, will cause the light to experience a rapidly changing refractive index on the transmission path, which in turn causes random fluctuations in light intensity, the so-called light intensity flicker phenomenon. This flicker will cause the instability of the received signal, thereby causing the problem of signal fading. The three effects of absorption, scattering and turbulence work together to not only reduce the signal light power reaching the receiving end, but also seriously affect the transmission performance and reliability of the entire underwater wireless optical communication system.

[0004] In the underwater turbulent channel modeling, models such as the log-normal (LN, Log-Normal) distribution, the generalized gamma (GGD, Generalized Gamma) distribution, and the mixture exponential generalized gamma distribution (Mixture Exponential-Generalized Gamma) have been proposed to simulate the impact of turbulence effects. Among them, the log-normal distribution and the generalized gamma distribution can only simulate the turbulence conditions in some special scenarios very well, while the mixture exponential generalized gamma distribution can fit most turbulence scenarios, including weak to strong turbulence, and this model can be used to derive a closed-form expression for the performance of the communication system. Therefore, a large number of underwater wireless optical communication fields use the mixture exponential generalized gamma function for research.

[0005] However, in more complex turbulence scenarios, especially when the random distribution of received light intensity is a bimodal distribution, the fitting accuracy of the mixed exponential generalized gamma will be severely reduced and will not be able to truly reflect the actual turbulence conditions. In this case, the closed-form expression of the communication system performance calculated using the model parameters will also have errors, which will greatly reduce the evaluation performance analysis and improvement effects of the subsequent communication system.

[0006] Therefore, it is of great significance for the research and development of underwater wireless optical communications to establish a turbulence statistical distribution model that is applicable to more turbulence scenarios and has better fitting effects and to derive a calculation method for its communication system performance. Summary of the invention

[0007] In order to overcome the shortcomings of the prior art, the present invention provides a turbulence model for underwater wireless optical communication and a method for calculating the performance of a communication system. A new turbulence statistical distribution model is established under the conditions of ocean turbulence, and the expression of the flicker index of the model is obtained by combining the model parameters. The Meijer-G function and the Fox-H function are used to obtain the closed-form expressions of the interruption probability and the bit error rate under the conditions of the model, so as to study the influence of different scenario parameters on the transmission performance of the system. Compared with the existing turbulence model, the present invention is closer to the complex turbulence environment of the ocean, especially in the complex turbulence scene with bimodal distribution, and can better realize the simulation study of the real ocean environment.

[0008] The technical solution adopted by the present invention to solve the technical problem is as follows:

[0009] Step 1: Establish a new double generalized gamma turbulence statistical distribution model;

[0010] Step 2: Combine the parameters of the double generalized gamma turbulence statistical distribution model to derive the expression of the scintillation index under the model conditions;

[0011] Step 3: Based on the definition of interruption probability and the integral of Meijer-G function, the closed-form expression of interruption probability under the condition of double generalized gamma turbulence statistical distribution model is derived;

[0012] Step 4: Based on the underwater wireless optical communication turbulence statistical distribution model and the communication system performance calculation method, the bit error rate formula of different modulation schemes is used, combined with the Fox-H function integral formula, to obtain the closed-form expression of the average bit error rate of different communication system modulation schemes under the condition of the double generalized gamma turbulence statistical model.

[0013] Furthermore, the step 1 is specifically as follows:

[0014] The light signal emitted by the transmitter is subjected to the turbulent channel, so the light intensity reaching the receiver is a randomly distributed variable. Therefore, the random distribution of the light intensity at the receiver is represented by the sum of two independent generalized gamma distribution functions, and these two generalized gamma functions are assigned different weights. The probability density mathematical expression f(I) of the new double generalized gamma turbulence statistical distribution model is:

[0015] f(I)=ωg1(I;[a1,b1,c1])+(1-ω)g2(I;[a2,b2,c2]) (1)

[0016]

[0017] Where I is the random variable of light intensity, g1(I; [a1, b1, c1]), g2(I; [a2, b2, c2]) and g(I; [a, b, c]) are generalized gamma distribution functions, [a1, b1, c1], [a2, b2, c2] and [a, b, c] are the parameters of g1(.), g2(.) and g(.) respectively; ω is the mixing weight coefficient of g1(.) and g2(.), and 0≤ω≤1; Γ(·) is the gamma function.

[0018] Furthermore, the step 2 is specifically as follows:

[0019] Step 2-1: Based on the definition of flicker index To calculate the flicker index under model conditions, we need to calculate E[I 2 ] and E[I], first derive the expected value of the nth power of the light intensity I under the distribution of this model The result is:

[0020]

[0021] Step 2-2: E[I n ] Take n = 1 and n = 2 as the calculation results and put them into the flicker index In the definition of , the expression of the scintillation index under the double generalized gamma turbulence statistical distribution model is derived, and the specific result is:

[0022]

[0023] Step 2-3: Normalize the expected light intensity I, that is, E[I] = 1, and the expression of the flicker index is further simplified to:

[0024]

[0025] Furthermore, the step 3 is specifically as follows:

[0026] Step 3-1: Assuming that the laser propagates in a dual generalized gamma distribution turbulence statistical distribution model channel, and the noise in the channel is Gaussian white noise, the signal at the receiving end is:

[0027] y=ηIx+N1 (6)

[0028] Where η is the photoelectric conversion efficiency, x is the transmitted information bit, n1 is the Gaussian noise with a mean of 0 and a variance of N0 / 2, and N0 represents the noise power;

[0029] Step 3-2: Define the instantaneous signal-to-noise ratio γ = (ηI) r / N0, when the detection mode is intensity detection, r = 2, when the detection mode is heterodyne detection, r = 1; then the average electrical noise ratio is μ r =(ηE(I)) r / N0, combined with the expression of Meijer-G function, the probability density function of the signal-to-noise ratio under the double generalized gamma turbulence distribution model is obtained as follows:

[0030]

[0031] in is the Meijer-G function;

[0032] Step 3-3: According to the definition of outage probability, it means that the instantaneous signal-to-noise ratio γ is less than the detection threshold γ th The probability is:

[0033] P out =P[γ<γ th ]=F γ (γ th ) (8)

[0034] Among them, F γ (γ th ) is f γ (γ th )’s cumulative distribution function, f γ (γ th) is integrated over γ, and the closed-form expression of the interruption probability under the condition of the double generalized gamma turbulence statistical distribution model is obtained:

[0035]

[0036] in, is the Meijer-G function.

[0037] Furthermore, the step 4 is specifically as follows:

[0038] The expression of the unified average bit error rate of different communication system modulation schemes is:

[0039]

[0040] Among them, δ, z, p, q k The value of depends on different modulation methods. This expression can uniformly represent the bit error rate of different digital modulation methods including intensity detection and heterodyne detection.

[0041] Substituting the signal-to-noise ratio probability density function of the double generalized gamma turbulence statistical distribution model into P e With the help of the properties and representation of the Fox-H function integral, the closed-form expression of the unified average bit error rate of OOK, MPSK, and M-QAM modulation under this model condition is:

[0042]

[0043] in, is the Fox-H function.

[0044] A computer program enables a computer to execute the above turbulence model and communication system performance calculation method.

[0045] An electronic device comprises: a processor and a memory; the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device executes the above-mentioned turbulence model and communication system performance calculation method.

[0046] A computer-readable storage medium stores a computer program, which implements the above-mentioned turbulence model and communication system performance calculation method when executed by a processor.

[0047] A chip includes: a processor for calling and running a computer program from a memory, so that a device equipped with the chip executes the above-mentioned turbulence model and communication system performance calculation method.

[0048] A computer program product, the computer program product comprising a computer storage medium storing a computer program, the computer program comprising instructions executable by at least one processor, and the turbulence model and communication system performance calculation method are implemented when the instructions are executed by the at least one processor.

[0049] The beneficial effects of the present invention are as follows:

[0050] The present invention provides a turbulence model for underwater wireless optical communication and a method for calculating the performance of a communication system. The established dual generalized gamma turbulence statistical distribution model is closer to the complex turbulence environment of the ocean than the existing turbulence model, especially in the complex turbulence scene with bimodal distribution, and can better realize the simulation research of the real ocean environment. Combined with the parameters of the dual generalized gamma turbulence statistical distribution model, the flicker index, interruption probability, and bit error rate of each modulation mode under the model conditions are derived, which provides convenience for analyzing the performance of underwater wireless optical communication systems in different scenarios.

[0051] The turbulence model proposed in this invention was used for experiments and simulations, and a bubble-induced turbulence experimental scene was built. Through actual data analysis, the fitting effects of each model were finally obtained as follows: Figure 3 , as shown in FIG4 , and it can be concluded that compared with the existing turbulence model, the model proposed in the present invention has the best fitting accuracy and can most realistically reflect the turbulence channel.

[0052] Combining the calculation method of the flicker index under the turbulence model proposed in the present invention and the model parameters obtained in the experimental scenario, the flicker index of each model is calculated. By comparing the actual flicker index under the experiment, the flicker index calculation value of the turbulence model proposed in the present invention is closer to the actual value, with a smaller error, and the effect is as follows: Figure 5 And as shown in Table 2.

[0053] Combined with the calculation method of the communication system performance under the turbulence model proposed in the present invention and the model parameters obtained in the experimental scenario, the derived interruption probability and bit error rate values ​​are calculated, and simulated by Monte Carlo simulation. The results show that the derived closed-form expression value is the same as the Monte Carlo simulation, which further verifies the correctness of the expression. The effect is shown in Figures 6 and 7. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 This is a schematic diagram of underwater wireless optical communication turbulence scene transmission involved in the present invention.

[0055] Figure 2 Schematic diagram of the experimental system of the present invention.

[0056] Figure 3The RMSE fitting result diagrams of different models under various turbulent conditions are provided for the embodiments of the present invention.

[0057] FIG4( a ) is a diagram showing measured data and fitting effects of various models under turbulent conditions with an air output of 2 L / min provided by an embodiment of the present invention.

[0058] FIG4( b ) is a diagram showing the actual measured data and the fitting effects of various models under turbulent conditions with an air output of 6 L / min provided by an embodiment of the present invention.

[0059] FIG4( c ) is a diagram showing measured data and fitting effects of various models under turbulent conditions with an air output of 10 L / min provided by an embodiment of the present invention.

[0060] FIG4( d ) is a diagram showing the measured data and the fitting effects of various models under turbulent conditions with an air output of 14 L / min provided by an embodiment of the present invention.

[0061] FIG4( e ) is a diagram showing the measured data and the fitting effects of various models under turbulent conditions with an air output of 18 L / min provided by an embodiment of the present invention.

[0062] Figure 5 The present invention provides a graph of the flicker index measured under various turbulent conditions and the flicker index calculated by the EGG and DGG models.

[0063] FIG6( a ) is a curve showing theoretical and simulated values ​​of the DGG model intensity modulation interruption probability under different turbulence conditions provided by an embodiment of the present invention.

[0064] FIG6( b ) is a curve showing theoretical and simulated values ​​of the DGG model heterodyne modulation interruption probability under different turbulence conditions provided by an embodiment of the present invention.

[0065] FIG. 7( a ) is a graph showing theoretical and simulated average bit error rate curves of different modulation modes in an environment with an air volume of 18 L / min, provided by an embodiment of the present invention.

[0066] FIG. 7( b ) is a curve of theoretical and simulated average bit error rates of the BPSK modulation method under different turbulent environments provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0067] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0068] The existing turbulence model has reduced fitting accuracy in complex turbulent environments and cannot truly simulate actual turbulence conditions, resulting in deviations in the performance analysis of communication systems using existing model parameters. This will lead to deviations in the closed-form expression of communication system performance calculated based on the model parameters, thereby affecting the accuracy of subsequent evaluation and improvement of communication system performance. The present invention provides a turbulence model for underwater wireless optical communication and a method for calculating communication system performance. It aims to propose a new turbulence model to improve the fitting accuracy of actual turbulence, and at the same time obtain a closed-form expression of the communication system performance under the model.

[0069] The present invention provides a turbulence model for underwater wireless optical communication and a method for calculating the performance of a communication system. A new turbulence statistical distribution model is established under the conditions of ocean turbulence, and the expression of the flicker index of the model is obtained by combining the model parameters. The closed-form expressions of the interruption probability and bit error rate under the conditions of the model are obtained by using the Meijer-G function and the Fox-H function, so that the influence of different scenario parameters on the transmission performance of the system can be studied.

[0070] In order to achieve the above technical objectives, the following steps are taken:

[0071] Step 1: Establish a new dual generalized gamma (DGG) turbulence statistical distribution model.

[0072] The light signal emitted by the transmitter is subjected to the turbulent channel, so the light intensity reaching the receiver is a randomly distributed variable. Therefore, the random distribution of the light intensity at the receiver is represented by the sum of two independent generalized gamma distribution functions, and these two generalized gamma functions are assigned different weights. The mathematical expression of the probability density of the model f(I) is:

[0073] f(I)=ωg1(I;[a1,b1,c1])+(1-ω)g2(I;[a2,b2,c2]) (12)

[0074]

[0075] Step 2: Combine the parameters of the double generalized gamma turbulence statistical distribution model to derive the expression of the scintillation index under the model conditions.

[0076] According to the definition of flicker index To calculate the flicker index under model conditions, we need to calculate E[I 2 ] and E[I], first derive the expected value of the nth power of the light intensity I under the distribution of this model, The result is:

[0077]

[0078] Will E[I n ] and take n = 1 and n = 2 to enter the flicker index In the definition of , the expression of the scintillation index under the double generalized gamma turbulence statistical distribution model is derived, and the specific results are:

[0079]

[0080] In order to facilitate data processing, the expected light intensity I is usually normalized, that is, E[I] = 1, and the expression of the flicker index is further simplified to:

[0081]

[0082] Step 3: Based on the definition of outage probability and the integral of the Meijer-G function, the closed-form expression of the outage probability under the double generalized gamma turbulence statistical distribution model is derived, including:

[0083] Assuming that the laser propagates in a dual generalized gamma distribution turbulence statistical distribution model channel, and the noise in the channel is Gaussian white noise, the signal at the receiving end is:

[0084] y=ηIx+N1 (17)

[0085] Where η is the photoelectric conversion efficiency, x is the transmitted information bit, N1 is the Gaussian white noise with a mean of 0 and a variance of N0 / 2, and N0 represents the noise power.

[0086] Define the instantaneous signal-to-noise ratio γ = (ηI) r / N0, when the detection method is intensity detection, r = 2, when the detection method is heterodyne detection, r = 1. Then the average electrical noise ratio is μ r =(ηE(I)) r / N0, combined with the expression of Meijer-G function, the probability density function of the signal-to-noise ratio under the double generalized gamma turbulence distribution model is obtained as follows:

[0087]

[0088] According to the definition of outage probability, the outage probability refers to the instantaneous signal-to-noise ratio γ being less than the detection threshold γ th The probability is:

[0089]

[0090] Among them, F γ (γ th ) is f γ (γ th )’s cumulative distribution function, fγ (γ th ) is integrated over γ, and the closed-form expression of the interruption probability under the condition of the double generalized gamma turbulence statistical distribution model is obtained:

[0091]

[0092] Step 4: Based on the underwater wireless optical communication turbulence statistical distribution model and the communication system performance calculation method, the bit error rate formula of different modulation schemes is used, combined with the Fox-H function integral formula, to obtain the closed-form expression of the average bit error rate of different communication system modulation schemes under the condition of the double generalized gamma turbulence statistical model. Specifically including:

[0093] The expression of the unified average bit error rate of different modulation schemes is:

[0094]

[0095] Among them, δ, z, p, q k The value of depends on different modulation methods. This expression can uniformly represent the bit error rate of different digital modulation methods including intensity detection and heterodyne detection. The specific value is:

[0096] Table 1 Parameters of different digital modulation methods

[0097]

[0098] Substituting the signal-to-noise ratio probability density function of the double generalized gamma turbulence statistical distribution model into P e In the integrated form, with the help of the properties and representation of the Fox-H function integral, the closed-form expression of the unified average bit error rate of OOK, MPSK, and M-QAM modulation under the model condition is:

[0099]

[0100] Example:

[0101] Step 1: Set up the experimental scene, see Figure 2 The system experimental framework diagram is shown in Figure 1. The blue-green laser is emitted by the LD laser transmitter, and the bubble generator generates bubble turbulence conditions. After the laser passes through the turbulent channel, an optical power meter is used at the receiving end to detect the received light intensity, and the data is saved in the computer for processing. It should be noted that this experimental scene setting is only for verifying the method proposed in this invention, and it is not special. Researchers can also change the experimental condition settings according to their needs.

[0102] In this experiment, the intensity of turbulence is controlled according to the gas output of the air pump, that is, the number of bubbles in the channel. The gas output of the bubbles is divided into five levels: 2L / min, 6L / min, 10L / min, 14L / min and 18L / min. Under each turbulent condition, 5000 light intensity values ​​are collected using an optical power meter. In order to ignore the propagation loss of the laser, the mean value of the light intensity under each group of conditions is normalized to 1.

[0103] Step 2: The light intensity distribution diagram under each set of turbulent conditions is obtained through the measured data, and the LN, GGD, EGG and the dual generalized gamma turbulence distribution model proposed in the present invention are used for fitting. In order to evaluate the fitting effect of each model, the RMSE index is used for evaluation. The RMSE can reflect the relationship between the measured value and the model prediction value. The specific expression is:

[0104]

[0105] Among them, f m,i and f p,i Represent the measured value and the model predicted value, respectively. N represents the number of samples. The closer the RMSE value is to 0, the smaller the error between the model and the measured value. At the same time, the flicker index of each model and the measured flicker index are calculated to verify which model is closer to the measured value. The following table is the measured data:

[0106] Table 2 Flicker index and RMSE of each model under experimental conditions

[0107]

[0108] Combined with the flicker index calculation formula proposed in this model, the above table and Figure 5 From the data, we can see that the scintillation index predicted by the LN model and the GGD model is too different from the actual value, while the EGG and DGG models are less different from the measured values ​​under various turbulent conditions. Among them, the DGG model proposed in the present invention is closer to the measured value and has the best effect.

[0109] Combine the data in the table with Figure 3 It can be seen from the data in FIG4 that the RMSE value of the DGG model proposed in the present invention is smaller than that of other models under various turbulent conditions, and the fitting effect is the best, which is closer to the actual turbulent situation.

[0110] Step 3: This simulation uses the DGG model parameters under various turbulent conditions measured by the above experiments, generates a large number of light intensity values ​​that conform to the model distribution through the Monte Carlo method, and substitutes each light intensity value into the system with different detection thresholds to calculate the interruption probability. Finally, the average interruption probability of the simulation under different turbulent conditions is obtained, and the model parameters are substituted into the derived interruption probability formula.

[0111] The results are shown in Figure 6. The Monte Carlo simulation results under various turbulent conditions are consistent with the expression results derived by the present invention, which proves the correctness of the expression. It can be seen that the smaller the detection threshold is, the more sensitive it is, and the smaller the interruption probability is. As the turbulent conditions become more and more complex, the interruption probability under the same detection threshold is higher. At the same time, it can be seen that the interruption probability of intensity modulation is higher than that of heterodyne modulation under the same conditions.

[0112] Step 4: This simulation uses the DGG model parameters measured in the above experiments under various turbulence conditions, generates a large number of light intensity values ​​that conform to the model distribution through the Monte Carlo method, and substitutes each light intensity value into the system with different modulation modes to calculate the average bit error rate. Finally, the average bit error rate of the Monte Carlo simulation under different turbulence conditions is obtained. At the same time, the model parameters are substituted into the derived bit error rate formula to calculate the bit error rate of the closed-form expression.

[0113] As can be seen from Figure 7, the Monte Carlo simulation results under various turbulence conditions are consistent with the expression results derived by the present invention, proving the correctness of the expression, and it can be seen that with the improvement of the signal-to-noise ratio, the bit error rate under each modulation mode decreases; under the same modulation mode and signal-to-noise ratio, as the turbulence conditions become more and more complex, the system bit error rate is higher. At the same time, it can be seen that under the same conditions, the bit error rate of BPSK is the lowest, and the bit error rate of 16QAM is the highest.

Claims

1. A turbulence model for underwater wireless optical communication and a method for calculating the performance of a communication system, characterized in that: The steps include: Step 1: Establish a new double generalized gamma turbulence statistical distribution model; Step 2: Combine the parameters of the double generalized gamma turbulence statistical distribution model to derive the expression of the scintillation index under the model conditions; Step 3: Based on the definition of interruption probability and the integral of Meijer-G function, the closed-form expression of interruption probability under the condition of double generalized gamma turbulence statistical distribution model is derived; Step 4: Based on the underwater wireless optical communication turbulence statistical distribution model and the communication system performance calculation method, the bit error rate formula of different modulation schemes is used, combined with the Fox-H function integral formula, to obtain the closed-form expression of the average bit error rate of different communication system modulation schemes under the condition of the double generalized gamma turbulence statistical model.

2. According to claim 1, a turbulence model for underwater wireless optical communication and a method for calculating communication system performance, characterized in that: The step 1 is specifically as follows: The light signal emitted by the transmitter is subjected to the turbulent channel, so the light intensity reaching the receiver is a randomly distributed variable. Therefore, the random distribution of the light intensity at the receiver is represented by the sum of two independent generalized gamma distribution functions, and these two generalized gamma functions are assigned different weights. The probability density mathematical expression f(I) of the new double generalized gamma turbulence statistical distribution model is: f(I)=ωg1(I;[a1,b1,c1])+(1-ω)g2(I;[a2,b2,c2])(1) Where I is the random variable of light intensity, g1(I; [a1, b1, c1]), g2(I; [a2, b2, c2]) and g(I; [a, b, c]) are generalized gamma distribution functions, [a1, b1, c1], [a2, b2, c2] and [a, b, c] are the parameters of g1(.), g2(.) and g(.) respectively; ω is the mixing weight coefficient of g1(.) and g2(.), and 0≤ω≤1; Γ(·) is the gamma function.

3. The turbulence model of underwater wireless optical communication and the method for calculating the performance of the communication system according to claim 2, characterized in that: The step 2 is specifically as follows: Step 2-1: Based on the definition of flicker index To calculate the flicker index under model conditions, we need to calculate E[I 2 ] and E[I], first derive the expected value of the nth power of the light intensity I under the distribution of this model The result is: Step 2-2: E[I n ] Take n = 1 and n = 2 as the calculation results and put them into the flicker index In the definition of , the expression of the scintillation index under the double generalized gamma turbulence statistical distribution model is derived, and the specific result is: Step 2-3: Normalize the expected light intensity I, that is, E[I] = 1, and the expression of the flicker index is further simplified to:

4. The turbulence model of underwater wireless optical communication and the method for calculating the performance of the communication system according to claim 3, characterized in that: The step 3 is specifically as follows: Step 3-1: Assuming that the laser propagates in a dual generalized gamma distribution turbulence statistical distribution model channel, and the noise in the channel is Gaussian white noise, the signal at the receiving end is: y=ηIx+N1 (6) Where η is the photoelectric conversion efficiency, x is the transmitted information bit, N1 is the Gaussian noise with a mean of 0 and a variance of N0 / 2, and N0 represents the noise power; Step 3-2: Define the instantaneous signal-to-noise ratio γ = (ηI) r / N0, when the detection mode is intensity detection, r = 2, when the detection mode is heterodyne detection, r = 1; then the average electrical noise ratio is μ r =(ηE(I)) r / N0, combined with the expression of Meijer-G function, the probability density function of the signal-to-noise ratio under the double generalized gamma turbulence distribution model is obtained as follows: in is the Meijer-G function; Step 3-3: According to the definition of outage probability, it means that the instantaneous signal-to-noise ratio γ is less than the detection threshold γ th The probability is: Among them, F γ (γ th ) is f γ (γ th )’s cumulative distribution function, f γ (γ th ) is integrated over γ, and the closed-form expression of the interruption probability under the condition of the double generalized gamma turbulence statistical distribution model is obtained: in, is the Meijer-G function.

5. The turbulence model of underwater wireless optical communication and the method for calculating the performance of the communication system according to claim 4, characterized in that: The step 4 is specifically as follows: The expression of the unified average bit error rate of different communication system modulation schemes is: Among them, δ, z, p, q k The value of depends on different modulation methods. This expression can uniformly represent the bit error rate of different digital modulation methods including intensity detection and heterodyne detection. Substituting the signal-to-noise ratio probability density function of the double generalized gamma turbulence statistical distribution model into P e In the integrated form, with the help of the properties and representation of the Fox-H function integral, the closed-form expression of the unified average bit error rate of OOK, MPSK, and M-QAM modulation under the model condition is: in, is the Fox-H function.

6. A computer program, characterized in that The computer program enables a computer to execute the method according to any one of claims 1 to 5.

7. An electronic device, characterized in that: include: Processor and memory; The memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device executes the method as claimed in any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

9. A chip, characterized in that: include: A processor, configured to call and run a computer program from a memory, so that a device equipped with the chip executes a method as claimed in any one of claims 1 to 5.

10. A computer program product, characterized in that The computer program product comprises a computer storage medium storing a computer program, wherein the computer program comprises instructions executable by at least one processor, and when the instructions are executed by the at least one processor, the method according to any one of claims 1 to 5 is implemented.

Images