A performance evaluation method and system for a LEO satellite-assisted deep space communication system

Abstract

The present invention provides a performance evaluation method and system for a LEO satellite-assisted deep space communication system, wherein the LEO satellite-assisted deep space communication system includes a detector, a LEO satellite and a ground terminal, wherein the detector and the LEO satellite communicate via an FSO link, and the LEO satellite and the ground terminal communicate via an RF link, wherein the method includes: in the design stage of the LEO satellite-assisted deep space communication system, obtaining index parameters affecting the communication quality of the FSO link, including coronal turbulence intensity parameters, pointing error parameters and solar noise parameters; and index parameters affecting the communication quality of the RF link, including shadow intensity parameters, LEO satellite position parameters and molecular absorption coefficients; inputting the index parameters into a constructed deep space communication system performance evaluation model to obtain performance indicators, wherein the performance indicators include interruption probability, channel capacity and bit error rate; and evaluating the performance of the deep space communication system according to the performance indicators. The method can evaluate the performance of the deep space communication system more comprehensively and accurately.

Description

Technical Field

[0001] The present invention belongs to the technical field of deep space communication, and in particular relates to a performance evaluation method and system for a LEO satellite-assisted deep space communication system. Background Art

[0002] Recently, with the surge in the number of Low Earth Orbit Satellite (LEO) satellites, relay communication assisted by LEO satellites is regarded as one of the promising future deep space communication technologies due to its lower communication latency, higher transmission rate and wider coverage.

[0003] In the early stage of design of LEO satellite-assisted deep space communication systems, accurate evaluation of system performance is of great significance for system design and optimization. Due to the complex and changeable deep space communication environment, existing methods often consider relatively single factors when calculating system performance indicators, resulting in the performance evaluation of LEO satellite-assisted deep space communication systems being not accurate and comprehensive enough. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides a performance evaluation method and system for a LEO satellite-assisted deep space communication system.

[0005] In order to achieve the above object, the present invention provides the following technical solutions:

[0006] A performance evaluation method for a LEO satellite-assisted deep space communication system, the LEO satellite-assisted deep space communication system comprising a detector, a LEO satellite and a ground terminal, the detector and the LEO satellite communicate via an FSO link, and the LEO satellite and the ground terminal communicate via an RF link, the method comprising:

[0007] In the design phase of the LEO satellite-assisted deep space communication system, the designed index parameters that affect the communication quality of the deep space communication system are obtained; wherein the index parameters include coronal turbulence intensity parameter, pointing error parameter, solar noise parameter, shadow intensity parameter, LEO satellite position parameter and molecular absorption coefficient; the coronal turbulence intensity parameter, pointing error parameter and solar noise parameter respectively characterize the influence of coronal turbulence, alignment deviation between the detector and the LEO satellite and solar noise on the FSO link signal-to-noise ratio; the shadow intensity parameter, LEO satellite position parameter and molecular absorption coefficient respectively characterize the influence of small-scale fading, LEO satellite position change and atmospheric molecular absorption on the RF link signal-to-noise ratio;

[0008] Inputting the index parameters into the constructed deep space communication system performance evaluation model to obtain performance indicators, wherein the performance indicators include interruption probability, channel capacity and bit error rate;

[0009] Evaluate the performance of deep space communication systems based on performance indicators.

[0010] Optionally, the deep space communication system performance evaluation model includes a first cumulative distribution function CDF of the system signal-to-noise ratio and a first probability density function PDF of the system signal-to-noise ratio. The process of constructing the deep space communication system performance evaluation model includes:

[0011] Constructing a second CDF and a second PDF of the FSO link signal-to-noise ratio, and a third CDF and a third PDF of the RF link signal-to-noise ratio, respectively;

[0012] The first CDF is constructed based on the second CDF and the third CDF. The expression of the first CDF is:

[0013] ;

[0014] in, represents the end-to-end signal-to-noise ratio of the deep space communication system, represents the second CDF, represents the third CDF;

[0015] The first PDF is constructed based on the second PDF and the third PDF. The expression of the first PDF is:

[0016] ;

[0017] in, represents the second PDF, Represents the third PDF.

[0018] Optionally, constructing a second CDF and a second PDF of the FSO link signal-to-noise ratio includes:

[0019] The CDF and PDF of the FSO link turbulence fading coefficient are constructed through the EW distribution model; the PDF of the pointing error fading coefficient is constructed through the Beckmann distribution model;

[0020] Based on the PDF of the turbulence fading coefficient and the PDF of the pointing error fading coefficient, a joint PDF including turbulence fading and pointing error fading is constructed as the second PDF;

[0021] Integrate the joint PDF to obtain the second CDF.

[0022] Optionally, constructing a third CDF and a third PDF of the RF link signal-to-noise ratio includes:

[0023] The propagation loss is modeled by the Friis equation to obtain the propagation loss coefficient; the molecular absorption coefficient is obtained by following the Beer-Lambert law; the small-scale fading is modeled by the SR distribution model to obtain the CDF and PDF of the small-scale fading; the CDF and PDF of the distance between the LEO satellite and the earth are constructed;

[0024] A third CDF and a third PDF of the RF link signal-to-noise ratio are constructed based on the propagation loss coefficient, the molecular absorption coefficient, the CDF and PDF of small-scale fading, and the CDF and PDF of the distance between the LEO satellite and the earth.

[0025] The present invention also provides a performance evaluation system for a LEO satellite-assisted deep space communication system, the LEO satellite-assisted deep space communication system comprising a detector, a LEO satellite and a ground terminal, the detector and the LEO satellite communicate via an FSO link, and the LEO satellite and the ground terminal communicate via an RF link, including:

[0026] An acquisition module is used to acquire the designed index parameters affecting the communication quality of the deep space communication system during the design phase of the LEO satellite-assisted deep space communication system; wherein the index parameters include coronal turbulence intensity parameter, pointing error parameter, solar noise parameter, shadow intensity parameter, LEO satellite position parameter and molecular absorption coefficient; the coronal turbulence intensity parameter, pointing error parameter and solar noise parameter respectively characterize the influence of coronal turbulence, alignment deviation between the detector and the LEO satellite and solar noise on the FSO link signal-to-noise ratio; the shadow intensity parameter, LEO satellite position parameter and molecular absorption coefficient respectively characterize the influence of small-scale fading, LEO satellite position change and atmospheric molecular absorption on the RF link signal-to-noise ratio;

[0027] An input module is used to input the index parameters into the constructed deep space communication system performance evaluation model to obtain performance indicators, wherein the performance indicators include interruption probability, channel capacity and bit error rate;

[0028] The evaluation module is used to evaluate the performance of the deep space communication system according to the performance indicators.

[0029] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the performance evaluation method of the above-mentioned LEO satellite-assisted deep space communication system when executing the program.

[0030] The present invention also provides a computer-readable storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the performance evaluation method of the LEO satellite-assisted deep space communication system is implemented.

[0031] The performance evaluation method of the LEO satellite-assisted deep space communication system provided by the present invention has the following beneficial effects:

[0032] In the present invention, during the design stage of the deep space communication system, the influence of pointing error, coronal turbulence and solar noise on the communication quality of the FSO link, as well as the influence of LEO satellite position change, molecular absorption in the atmosphere and small-scale fading on the communication quality of the RF link are taken into consideration. By comprehensively considering various influencing factors and inputting these factors into the constructed deep space communication system performance evaluation model, performance indicators such as interruption probability, channel capacity and bit error rate are obtained. The performance indicators can more comprehensively and accurately reflect the performance of the deep space communication system under the actual working environment, thereby better optimizing the deep space communication system to adapt to the complex and changeable deep space communication environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiment of the present invention and its design scheme, the following briefly introduces the drawings required for this embodiment. The drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0034] Figure 1 An architecture diagram of a LEO satellite-assisted deep space communication system provided by an embodiment of the present invention;

[0035] Figure 2 A schematic flow chart of a performance evaluation method for a LEO satellite-assisted deep space communication system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0036] In order to enable those skilled in the art to better understand the technical solution of the present invention and implement it, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the scope of protection of the present invention.

[0037] In the description of the present invention, it is to be understood that the terms “center”, “longitudinal”, “lateral”, “length”, “width”, “thickness”, “up”, “down”, “front”, “back”, “left”, “right”, “vertical”, “horizontal”, “top”, “bottom”, “inside”, “outside”, “axial”, “radial”, “circumferential”, etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing the technical solutions of the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0038] In addition, the terms "first", "second", etc. are used for descriptive purposes only and are not to be understood as indicating or implying relative importance. In the description of the present invention, it should be noted that, unless otherwise clearly specified or limited, the terms "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances. In the description of the present invention, unless otherwise specified, "plurality" means two or more, which will not be described in detail here.

[0039] Before introducing the performance evaluation method of the LEO satellite-assisted deep space communication system provided by the present invention, Figure 1 The present invention introduces the LEO satellite-assisted deep space communication system.

[0040] like Figure 1 As shown in the figure, the LEO satellite-assisted deep space communication system includes a detector (S), a LEO satellite (R) and a ground terminal (D). The detector and the LEO satellite communicate through a free space optical (FSO) communication link, and the LEO satellite and the ground terminal communicate through a radio frequency (RF) communication link. The communication process of the system is as follows: the detector sends the encoded FSO signal to the LEO satellite through the FSO channel, the photoelectric converter of the LEO satellite converts the received optical signal into an electrical signal, and relays the electrical signal to the ground terminal through the RF channel. After the ground terminal node receives the electrical signal, it undergoes interference elimination processing to ensure the purity of the signal. Finally, the ground terminal node successfully receives the transmitted signal, and can subsequently perform signal demodulation, decoding and information restoration operations.

[0041] It should be understood that FSO communication links are affected by many factors in practical applications, among which pointing errors, coronal turbulence and solar noise are more significant factors.

[0042] Pointing errors arise from misalignment between the probe and the LEO satellite, which increases with the distance between the two and the motion of the LEO satellite.

[0043] Coronal turbulence refers to the turbulence caused by the activity of high-temperature and high-energy particles in the solar corona, which can cause refraction and scattering of optical signals during transmission, thereby distorting the signal waveform. This distortion may cause signal quality to deteriorate and affect the reception effect of the communication system. Changes in airflow and temperature gradients in coronal turbulence may cause the propagation path of optical signals to deviate, thereby increasing pointing errors.

[0044] Solar noise refers to the interference caused by solar radiation to FSO communications. In the case of interference from a high background noise field, it will cause the signal-to-noise ratio at the receiving end to be small, thus affecting the performance of the system.

[0045] It should also be understood that the high-speed movement of LEO satellites and the physical phenomena during their communications together cause significant large-scale and small-scale fading in the RF link. Specifically, the constant changes in the position of LEO satellites cause path loss, which is particularly prominent in the Ka-band. In this frequency band, when the signal passes through the atmosphere, it interacts with molecules in the atmosphere (such as water vapor, oxygen, etc.), causing the signal energy to be absorbed, which in turn exacerbates the attenuation of the signal. This molecular absorption phenomenon in high-frequency communications makes the signal attenuation problem more significant. Small-scale fading mainly comes from the rapid movement of LEO satellites, which causes rapid fluctuations in the signal, leading to problems such as channel fading, multipath interference, and signal blocking.

[0046] Currently, when building communication models to calculate system performance, the impact of the above-mentioned comprehensive factors on the data transmitted by FSO communication links and RF communication links is often ignored, resulting in inaccurate and incomplete system performance evaluation.

[0047] Therefore, based on the above-mentioned LEO satellite-assisted deep space communication system, the present invention proposes a performance evaluation method for a LEO satellite-assisted deep space communication system, such as Figure 2 As shown, the method comprises the following steps:

[0048] S1. During the design phase of a LEO satellite-assisted deep space communication system, the designed index parameters affecting the communication quality of the deep space communication system are obtained; wherein the index parameters include coronal turbulence intensity parameters, shadow intensity parameters, pointing error parameters, solar noise parameters, LEO satellite position parameters and molecular absorption coefficients.

[0049] It should be understood that during the design phase of a deep space communication system, some parameters need to be designed to evaluate the performance of the system in order to better optimize the system.

[0050] Among them, the coronal turbulence intensity parameter represents the impact of coronal turbulence on the FSO link signal-to-noise ratio. The coronal turbulence intensity can be divided into weak turbulence and moderate turbulence. The turbulence intensity can be measured by and express, and Is related to the flicker index The relevant shape parameters, and Different values ​​represent different coronal turbulence intensities.

[0051] The shadow intensity parameter characterizes the impact of small-scale fading on the signal-to-noise ratio of the RF link. The shadow intensity can be divided into mild shadow, average shadow and strong shadow. The shadow intensity can be measured by , and To express, for R - D The severity of the link degradation, for R - D The average power of the line-of-sight component of the link, for R - D The average power of the multipath component of the link, with different values, represents different shadow intensities. It should be understood that in a communication system, shadows can cause signal fading, a phenomenon known as the shadow effect. The shadow effect refers to the reflection of radio waves when they encounter an obstacle whose area is much larger than the wavelength of the electromagnetic wave, thereby forming a "shadow" area on the other side of the obstacle where the radio waves cannot directly propagate. When the terminal moves into the shadow area, the wireless signal needs to propagate through other paths, which will cause the received signal strength in the shadow area to decrease, forming shadow fading.

[0052] Table 1 Values ​​corresponding to different decay conditions

[0053]

[0054] Table 1 is an example of values ​​corresponding to different decay conditions. In the early stage of system design, different decay conditions can be set according to the values ​​in Table 1.

[0055] The pointing error parameter characterizes the effect of the alignment deviation between the detector and the LEO satellite on the signal-to-noise ratio of the FSO link. The pointing error parameter is given by , , and To express, is the jitter of horizontal displacement, is the jitter of vertical displacement, is the axis error of the horizontal axis of the receiving plane, is the boresight error of the elevation axis of the receiving plane.

[0056] The solar noise parameter characterizes the impact of solar noise on the signal-to-noise ratio of the FSO link and can be calculated from the solar spectrum irradiance. and the optical bandwidth of the solar spectrum entering the receiver B v To express.

[0057] The LEO satellite position parameter characterizes the impact of the LEO satellite position change on the RF link signal-to-noise ratio. It can be obtained by the minimum distance of the LEO satellite from the earth's surface. d min and the satellite's elevation angle θ To express.

[0058] Table 2 Setting of indicator parameters

[0059]

[0060] It should be understood that Table 2 is an example of a value of an indicator parameter, and in the actual design process, indicator parameters with other values ​​can also be designed.

[0061] S2, input the index parameters into the constructed deep space communication system performance evaluation model to obtain performance indicators, which include interruption probability, channel capacity and bit error rate.

[0062] Based on the influence of pointing error, coronal turbulence and solar noise on the signal-to-noise ratio of FSO link, and the influence of LEO satellite position change, molecular absorption in the atmosphere and small-scale fading on the signal-to-noise ratio of RF communication link, the present invention theoretically derives a deep space communication system performance evaluation model. The model can more comprehensively reflect the influence of various factors on the communication quality of the deep space communication system and realize a more comprehensive system performance evaluation.

[0063] Among them, the signal-to-noise ratio is an important indicator to measure signal quality. It is defined as the ratio of signal power to noise power. The signal-to-noise ratio is directly related to the performance of the communication system. A higher signal-to-noise ratio value means that the signal is clearer and contains less noise interference, while a lower signal-to-noise ratio value means that the signal quality is poor and the noise interference is greater.

[0064] The deep space communication system performance evaluation model includes the first cumulative distribution function (CDF) of the system signal-to-noise ratio and the first probability density function (PDF) of the system signal-to-noise ratio. Since the deep space communication system contains two communication links, the process of constructing the deep space communication system performance evaluation model includes:

[0065] A second CDF and a second PDF of the FSO link signal-to-noise ratio, and a third CDF and a third PDF of the RF link signal-to-noise ratio are constructed respectively, a first CDF is constructed according to the second CDF and the third CDF, and a first PDF is constructed according to the second PDF and the third PDF.

[0066] Next, the derivation process of the first CDF and the first PDF is introduced.

[0067] First, some parameters involved in the application of deep space communication systems are defined:

[0068] The end-to-end signal-to-noise ratio of a deep space communication system is defined as:

[0069] (1)

[0070] in, and are the signal-to-noise ratios of the PSO communication link (SR link) and the RF communication link (RD link), respectively.

[0071] The signal received by the LEO satellite relay can be expressed as:

[0072] (2)

[0073] in, represents the detector's responsivity, represents the transmission power of the FSO signal, Indicates the FSO link fading coefficient. is the input signal, satisfying (in represents the expectation operator), is zero and has a variance of Additive white Gaussian noise.

[0074] The present invention considers two types of noise, one type is the detector noise source, including thermal noise and shot noise. The other is the noise source caused by the sun, which consists of solar-local oscillator mixed noise and solar self-mixing noise. Among them, the spectral density of thermal noise and shot noise are respectively expressed as:

[0075] (3)

[0076] (4)

[0077] in, is the Boltzmann constant, T represents the noise temperature of the receiver, and R is the effective resistance of the thermal noise source. It is the basic unit of electric charge. is the responsivity of the receiver, P L is the local oscillator component of the incident light on the photodiode.

[0078] The spectral densities of the solar-local oscillator mixed noise and the solar self-mixing noise are expressed as:

[0079] (5)

[0080] (6)

[0081] in, , represents the aperture surface area that collects solar radiation, is the solar spectral irradiance, is the optical bandwidth of the solar spectrum entering the receiver.

[0082] It should be understood that the above noises are additive, so .

[0083] In the present invention, it is considered that the FSO link experiences signal fading due to coronal turbulence and pointing errors. Therefore, the combined fading coefficient of the FSO link is expressed as ;in, represents the turbulence attenuation coefficient, Represents the pointing error fading coefficient.

[0084] It should be understood that the turbulence characteristics of FSO communication links can be described by the Exponential Weibull (EW) distribution model, which can accurately capture the fading behavior under various turbulence conditions and is applicable to all aperture diameter averages under different turbulence scenarios. The EW distribution model can be used to derive The CDF of is:

[0085] (7)

[0086] The PDF is:

[0087] (8)

[0088] in, and Is related to the flicker index Related shape parameters; is the scale parameter, which is the average value of the irradiance related; Γ(·) is the Gamma function, exp(·) is the exponential function, yes S - R Link scale parameter.

[0089] The present invention takes into account the non-zero boresight pointing error, which follows the Beckmann distribution. This is because the random vibration of the receiver caused by the hovering fluctuation of the LEO satellite is taken into account. The Beckmann distribution model can be used to derive the error in the FSO link. The PDF is:

[0090] (9)

[0091] in, is the fraction of power collected when the radial displacement is zero, , erf(·) is the error function; , is the beam width, a is the receiver radius, , , is the equivalent beam width at the receiver, is the standard deviation of the pointing error displacement, , yes Axis direction pointing error displacement standard deviation, , yes Axis direction pointing error displacement standard deviation, , and is the ratio between the equivalent beam radius at the receiver and the standard deviation of the corresponding pointing error displacement (jitter), .

[0092] The communication link between the LEO satellite relay and the ground terminal, namely the RD link, is carried out through the radio frequency working in the Ka band. The receiving signal of the ground terminal can be expressed as:

[0093] (10)

[0094] in, is the transmission power of the Ka-band RF signal, is zero and has a variance of Additive Gaussian white noise. In the Ka band, is the fading coefficient between the LEO satellite and the ground terminal.

[0095] In the present invention, the Ka-band is used for radio frequency communication between RDs to take advantage of its high data transmission rate and compact antenna design, so that LEO satellites can provide higher communication bandwidth, reduce signal delay and support high-density data transmission. In addition, the high-frequency characteristics of the Ka-band enable satellite communication systems to achieve higher performance in a smaller spatial range, thereby improving the overall efficiency and data processing capabilities of the LEO satellite network. However, when operating in the Ka-band, the signal transmission of the RD link is affected by many factors. First, the signal will gradually attenuate as the distance increases during the transmission process, which is called attenuation loss, which depends on the frequency of the signal, the transmission distance and the characteristics of the propagation environment. Secondly, due to its high-frequency characteristics, the Ka-band signal will be affected by molecular absorption when passing through the atmosphere (including clouds or rain), resulting in further weakening of the signal strength. Finally, small-scale fading is also a factor that cannot be ignored, which describes the rapid fluctuation of signal strength in a short period of time due to local factors such as multipath effects, scattering or receiver movement. Therefore, the overall fading coefficient of the radio frequency channel, including path gain, molecular absorption and small-scale fading, can be expressed as .in, is the propagation loss coefficient, is the molecular absorption loss coefficient, is the small-scale fading coefficient.

[0096] for , can be modeled using the Friis equation and expressed as follows:

[0097] (11)

[0098] in, and Respectively expressed in r The gain of the transmitting and receiving antennas in the direction and opposite direction, W represents the carrier bandwidth, is the wavelength, is the altitude of the LEO satellite above the Earth's surface.

[0099] Molecular absorption follows the Beer-Lambert law, represents the molecular absorption loss coefficient, It is expressed as:

[0100] (12)

[0101] in, represents the molecular absorption coefficient, which is limited by the molecular absorption effect of the RD link, Defined as the effective path length. is the actual path length, δ Represents the effective path factor.

[0102] The small-scale fading of the RF link can be modeled using the Shadowed-Rician (SR) distribution model to describe the statistical distribution of the satellite link from R to D. The SR distribution model can be used to derive The CDF of is:

[0103] (13)

[0104] The PDF is:

[0105] (14)

[0106] in, , , , , .

[0107] The unified instantaneous signal-to-noise ratio of the FSO link can be expressed as , where , is the average signal-to-noise ratio of the FSO link.

[0108] Based on the above definition, the performance evaluation model of the deep space communication system is derived. First, the CDF and PDF of the signal-to-noise ratio of the FSO communication link are derived, that is, the second CDF and the second PDF are derived. The derivation process is as follows:

[0109] Performing mathematical operations on the above formulas (7) and (8), we can obtain The CDF of is:

[0110] (15)

[0111] The PDF is:

[0112] (16)

[0113] Similarly, from formula (9), we can get The PDF is:

[0114] (17)

[0115] FSO channel including coronal turbulence and pointing errors The joint PDF distribution can be derived from the following relationship:

[0116] (18)

[0117] in, .

[0118] Substituting equations (16) and (17) into equation (18), we get the signal-to-noise ratio PDF of the FSO link as follows:

[0119] (19)

[0120] By simplifying with the help of Newton's generalized binomial theorem, we can get the following formula:

[0121] (20)

[0122] Substituting equation (20) into equation (19), the signal-to-noise ratio PDF of the FSO link is rewritten as:

[0123] (twenty one)

[0124] Finally, using some simple mathematical operations, the integral in formula (21) is further transformed into a closed-form expression to obtain the second PDF, as follows:

[0125] (twenty two)

[0126] in, , .

[0127] Integrating equation (22) yields the CDF formula for the signal-to-noise ratio of the FSO link, expressed as:

[0128] (twenty three)

[0129] The Whittaker function in equation (23) is transformed into the generalized Meijer G function, and its closed-form expression is:

[0130] (twenty four)

[0131] Substituting equation (24) into equation (23), integrating the Meijer G function in equation (24), we get the second CDF as follows:

[0132] (25)

[0133] Further, the CDF and PDF of the signal-to-noise ratio of the RF communication link are derived, that is, the third CDF and the third PDF are derived, and the derivation process is as follows:

[0134] In the scenario of assuming communication with visible satellites, the present invention considers that the LEO satellite is at a distance from the earth's surface. km altitude, and the user is located on the surface of the Earth. Exceeding the masking elevation angle The satellite is visible to users only when the elevation angle of the LEO satellite is =90°, the distance between the user and the satellite reaches the minimum value, which is recorded as , which is equal to the deployment height On the contrary, when the satellite elevation angle is = When the distance reaches the maximum value. The maximum distance observed under , is the radius of the Earth.

[0135] In order to obtain the signal-to-noise ratio CDF of the RF communication link, the present invention first gives the actual path length between the LEO satellite and the earth. The CDF and PDF:

[0136] (26)

[0137] (27)

[0138] in, , is the orbital altitude.

[0139] For LEO satellite-aided deep space communication systems, It can be expressed as:

[0140] (28)

[0141] in, is the average signal-to-noise ratio of the RF link, , , , .

[0142] For LEO satellite-assisted deep space communication systems, the signal-to-noise ratio of the RF link The CDF of can be expressed as:

[0143] (29)

[0144] in, , represents the probability, express The PDF expression of .

[0145] After mathematical operations and simplification, The CDF and PDF of can be expressed as:

[0146] (30)

[0147] (31)

[0148] in, represents the Lambert function, that is The solution.

[0149] Substituting equation (13) and equation (31) into equation (23), we get The CDF of is:

[0150] (32)

[0151] Substituting formula (27) into formula (32), we get The CDF of can be further rewritten as:

[0152] (33)

[0153] According to Lambert The derivative formula of the function can be obtained Therefore, formula (33) can be further rewritten as:

[0154] (34)

[0155] Using the method of integration by parts, formula (34) can be further rewritten as:

[0156] (35)

[0157] in, and .

[0158] The derivative part in the above formula (35) can be simplified to , using the characteristics of Taylor series expansion, Lambert The function can be expressed as Substituting equation (14) into equation (35), after some mathematical operations, we get the following equation:

[0159] (36)

[0160] After mathematical operations and simplification, we can finally get Incomplete Gamma and Lambert of CDF The unified expression of the function, namely the third CDF, is as follows:

[0161]

[0162] (37)

[0163] in, , , , .

[0164] By comparing formula (37) Taking the derivative, we get the expression of the third PDF:

[0165] (38)

[0166] Through the above derivation process, the CDF and PDF of the FSO link signal-to-noise ratio, as well as the CDF and PDF of the RF link signal-to-noise ratio can be obtained. Since the LEO satellite-assisted deep space communication system in the present invention is composed of an FSO link and an RF link, the CDF and PDF of the signal-to-noise ratio of the complete LEO satellite-assisted deep space communication system can be derived.

[0167] Specifically, the CDF of the signal-to-noise ratio of the deep space communication system, that is, the first CDF, is:

[0168] (39)

[0169] in, and are the second CDF and the third CDF in equation (25) and equation (37), respectively.

[0170] use , we get the PDF of the signal-to-noise ratio of the deep space communication system, that is, the first PDF is:

[0171] (40)

[0172] in, and are the second and third PDFs in (22) and (38), respectively.

[0173] Above The derivation process of the CDF and PDF expressions is the derivation process of the first CDF and the first PDF in the deep space communication system performance evaluation model. The CDF and PDF expressions of , and the index parameters obtained in S1, can be used to further calculate the performance indicators of the deep space communication system, including the interruption probability, channel capacity and bit error rate, and then comprehensively evaluate the performance of the deep space communication system.

[0174] Specifically, the indicator parameters are input into the expression of the first CDF to calculate the interruption probability of the deep space communication system, and the indicator parameters are input into the expression of the first PDF to calculate the channel capacity and bit error rate of the deep space communication system.

[0175] The outage probability refers to the probability that the system performance is lower than the predetermined standard under a given signal-to-noise ratio threshold. The outage probability can be calculated by the following formula:

[0176] ;

[0177] in, is the outage probability, is the preset signal-to-noise ratio threshold, It can be calculated by the first CDF.

[0178] Channel capacity refers to the maximum rate at which a system can transmit information without error under given channel conditions. The average channel capacity can be calculated using the following formula:

[0179] ;

[0180] in, is the channel bandwidth, is the first PDF.

[0181] The bit error rate refers to the ratio of the number of bits received by the system in error to the total number of bits transmitted. The average bit error rate can be calculated using the following formula:

[0182] ;

[0183] in, yes function.

[0184] S3, by evaluating the performance of the deep space communication system according to performance indicators.

[0185] The interruption probability, channel capacity and bit error rate can be used to comprehensively evaluate the performance of the deep space communication system and thus optimize the system. For example, if the interruption probability is high, the system may need to be improved to reduce communication interruptions; if the channel capacity is low, the system may require a more efficient modulation scheme or a larger bandwidth; if the bit error rate is high, the system may require stronger error correction capabilities or improved receiver sensitivity.

[0186] The present invention is applicable to deep space communication scenarios based on LEO satellite assistance, and has important application value in deep space missions that require high precision and high reliability. For example, in the fields of deep space exploration, interplanetary communication, and deep space navigation, the present invention can be used to model and optimize deep space communication links. Compared with the prior art, the present invention has better scalability and adaptability, and can be widely used in different types of deep space missions and communication scenarios of ground control terminals.

[0187] Based on the same inventive concept, the present invention also provides a performance evaluation system for a LEO satellite-assisted deep space communication system. Exemplarily, the system includes:

[0188] An acquisition module is used to acquire the designed index parameters affecting the communication quality of the deep space communication system during the design phase of the LEO satellite-assisted deep space communication system; wherein the index parameters include coronal turbulence intensity parameters, pointing error parameters, solar noise parameters, shadow intensity parameters, LEO satellite position parameters and molecular absorption coefficients; the coronal turbulence intensity parameters, pointing error parameters and solar noise parameters respectively characterize the effects of coronal turbulence, alignment deviation between the detector and the LEO satellite and solar noise on the FSO link signal-to-noise ratio; the shadow intensity parameters, LEO satellite position parameters and molecular absorption coefficients respectively characterize the effects of shadow fading, LEO satellite position changes and atmospheric molecular absorption on the RF link signal-to-noise ratio.

[0189] The input module is used to input the index parameters into the constructed deep space communication system performance evaluation model to obtain performance indicators, which include interruption probability, channel capacity and bit error rate.

[0190] The evaluation module is used to evaluate the performance of the deep space communication system according to the performance indicators.

[0191] Each module in the performance evaluation system of the LEO satellite-assisted deep space communication system can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0192] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps in the embodiment of the performance evaluation method of the LEO satellite-assisted deep space communication system. The specific implementation method can be found in the method embodiment, which will not be repeated here.

[0193] Furthermore, the present invention also provides a non-temporary computer-readable storage medium containing instructions, and a computer program is stored on the storage medium. For example, a memory containing instructions, the above instructions can be executed by a processor of a computer device to complete the above method. For example, the non-temporary computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device. When the computer program is executed by the processor, the steps in the embodiment of the performance evaluation method of the LEO satellite-assisted deep space communication system can be implemented. The specific implementation method can be referred to the method embodiment, which will not be repeated here.

[0194] It should be understood by those skilled in the art that embodiments of the present invention may provide methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0195] The present invention is described with reference to flowcharts and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as a combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0196] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0197] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0198] It should be pointed out that the specific implementation methods described above can enable those skilled in the art to understand the invention more comprehensively, but do not limit the invention in any way. Therefore, although the invention has been described in detail in this specification and embodiments, those skilled in the art should understand that the invention can still be modified or replaced by equivalents; and all technical solutions and improvements that do not deviate from the spirit and scope of the invention are included in the protection scope of the invention. Any figure mark in the claims should not be regarded as limiting the claims involved. Any simple change or equivalent replacement of the technical solution that can be obviously obtained by any technician familiar with the field within the technical scope disclosed in the present invention belongs to the protection scope of the present invention.

Claims

1. A performance evaluation method for a LEO satellite-assisted deep space communication system, characterized in that: The LEO satellite-assisted deep space communication system includes a detector, a LEO satellite and a ground terminal, the detector and the LEO satellite communicate through an FSO link, and the LEO satellite and the ground terminal communicate through an RF link. The method includes: In the design phase of the LEO satellite-assisted deep space communication system, the designed index parameters that affect the communication quality of the deep space communication system are obtained; wherein the index parameters include coronal turbulence intensity parameter, pointing error parameter, solar noise parameter, shadow intensity parameter, LEO satellite position parameter and molecular absorption coefficient; the coronal turbulence intensity parameter, pointing error parameter and solar noise parameter respectively characterize the influence of coronal turbulence, alignment deviation between the detector and the LEO satellite and solar noise on the FSO link signal-to-noise ratio; the shadow intensity parameter, LEO satellite position parameter and molecular absorption coefficient respectively characterize the influence of small-scale fading, LEO satellite position change and atmospheric molecular absorption on the RF link signal-to-noise ratio; Inputting the index parameters into the constructed deep space communication system performance evaluation model to obtain performance indicators, wherein the performance indicators include interruption probability, channel capacity and bit error rate; Evaluate the performance of deep space communication systems based on performance indicators; The deep space communication system performance evaluation model includes the first cumulative distribution function CDF of the system signal-to-noise ratio and the first probability density function PDF of the system signal-to-noise ratio. The process of constructing the deep space communication system performance evaluation model includes: Constructing a second CDF and a second PDF of the FSO link signal-to-noise ratio, and a third CDF and a third PDF of the RF link signal-to-noise ratio, respectively; The first CDF is constructed based on the second CDF and the third CDF. The expression of the first CDF is: Where γ represents the end-to-end signal-to-noise ratio of the deep space communication system, represents the second CDF, represents the third CDF; The first PDF is constructed based on the second PDF and the third PDF. The expression of the first PDF is: in, represents the second PDF, represents the third PDF; Construct the second CDF and second PDF of the FSO link signal-to-noise ratio, including: The CDF and PDF of the FSO link turbulence fading coefficient are constructed through the EW distribution model; the PDF of the pointing error fading coefficient is constructed through the Beckmann distribution model; Based on the PDF of the turbulence fading coefficient and the PDF of the pointing error fading coefficient, a joint PDF including turbulence fading and pointing error fading is constructed as the second PDF; Integrate the joint PDF to obtain the second CDF; The expression of the second PDF is: In the formula, γ SR is the signal-to-noise ratio of the PSO communication link, is the average signal-to-noise ratio of the FSO link; and ψ SR Is related to the flicker index Related shape parameters; W represents the carrier bandwidth; represents the equivalent beam width at the receiver, σ mod represents the standard deviation of pointing error displacement; A0 represents the fraction of power collected when the radial displacement is zero, A0 = [erf(v)] 2 , erf(·) represents the error function; ω Z represents the beam width, and a represents the receiver radius; σ x Represents the jitter of horizontal displacement, σ y Represents the jitter of vertical displacement, μ x Represents the axis error of the horizontal axis of the receiving plane, μ y represents the boresight error of the elevation axis of the receiving plane, η SR represents the scale parameter of the SR link; is variable substitution, The expression of the second CDF is: In the formula, represents the Meijer G function; Construct the third CDF and third PDF of the RF link signal-to-noise ratio, including: The propagation loss is modeled by the Friis equation to obtain the propagation loss coefficient; the molecular absorption coefficient is obtained by following the Beer-Lambert law; the small-scale fading is modeled by the SR distribution model to obtain the CDF and PDF of the small-scale fading; the CDF and PDF of the distance between the LEO satellite and the earth are constructed; Constructing a third CDF and a third PDF of the RF link signal-to-noise ratio based on the propagation loss coefficient, the molecular absorption coefficient, the CDF and PDF of small-scale fading, and the CDF and PDF of the distance between the LEO satellite and the earth; The expression of the third CDF is: In the formula, γ RD is the signal-to-noise ratio of the RF communication link, is the average signal-to-noise ratio of the RF link; m RD Indicates the fading severity of the RD link; W indicates the carrier bandwidth; ζ represents the molecular absorption coefficient, δ represents the effective path factor; κ(·)=δ 2 · 2 e 2ψδ· ; Indicates when When d1=d min , d min Indicates the minimum distance between the user and the satellite. When d2=d max(θ) , d max (θ) represents the maximum distance observed under the masking elevation angle θ; m RD is the fading severity of the RD link, Ω RD is the average power of the line-of-sight component of the RD link, b RD is the average power of the multipath component of the RD link, d min represents the minimum distance between the user and the satellite, d max (θ) represents the maximum distance observed under the masking elevation angle θ; m RD is the fading severity of the RD link, Ω RD is the average power of the line-of-sight component of the RD link, b RD is the average power of the multipath component of the RD link; and represents the gain of the transmitting and receiving antennas in the r direction and the opposite direction respectively, K B =1.38×10 -23 J / K is the Boltzmann constant, T is the noise temperature of the receiver, W is the carrier bandwidth, and λ is the wavelength; The expression of the third PDF is:

2. A system for implementing the performance evaluation method of the LEO satellite-assisted deep space communication system as claimed in claim 1, characterized in that: The LEO satellite-assisted deep space communication system includes a probe, a LEO satellite and a ground terminal. The probe and the LEO satellite communicate through an FSO link, and the LEO satellite and the ground terminal communicate through an RF link, including: An acquisition module is used to acquire the designed index parameters affecting the communication quality of the deep space communication system during the design phase of the LEO satellite-assisted deep space communication system; wherein the index parameters include coronal turbulence intensity parameter, pointing error parameter, solar noise parameter, shadow intensity parameter, LEO satellite position parameter and molecular absorption coefficient; the coronal turbulence intensity parameter, pointing error parameter and solar noise parameter respectively characterize the influence of coronal turbulence, alignment deviation between the detector and the LEO satellite and solar noise on the FSO link signal-to-noise ratio; the shadow intensity parameter, LEO satellite position parameter and molecular absorption coefficient respectively characterize the influence of shadow fading, LEO satellite position change and atmospheric molecular absorption on the RF link signal-to-noise ratio; An input module is used to input the index parameters into the constructed deep space communication system performance evaluation model to obtain performance indicators, wherein the performance indicators include interruption probability, channel capacity and bit error rate; The evaluation module is used to evaluate the performance of the deep space communication system according to the performance indicators.

3. A computer device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the program, the performance evaluation method of the LEO satellite-assisted deep space communication system as claimed in claim 1 is implemented.

4. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by the processor, the performance evaluation method of the LEO satellite-assisted deep space communication system according to claim 1 is implemented.

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