Method and system for simulating multipath fading based on space-air-ground integrated network

Abstract

The embodiment of the present disclosure relates to a kind of based on space-air-ground integrated network multipath fading simulation method and system, the method comprises: based on the construction flat fading channel of sinusoidal superposition method, and the random process of flat fading channel is optimized, flat fading channel includes Rayleigh fading channel and Rician fading channel;According to target link type and the flat fading channel configuration target link corresponding basic fading model and scene simulation sub-network;Target link type includes space-based link, air-based link or ground-based link, and scene simulation sub-network includes ionospheric dispersion simulation unit, troposphere delay simulation unit and shadow fading simulation unit;Multipath fading simulation is carried out to target link using the basic fading model and scene simulation sub-network configured, and multipath fading simulation result is generated.The embodiment of the present disclosure is suitable for space-based, air-based, ground-based multipath fading simulation, solves the scene adaptation limitation of traditional method, while balancing simulation accuracy and real-time performance.

Description

Technical Field

[0001] This disclosure relates to the field of wireless communication technology, and in particular to a multipath fading simulation method and system based on an integrated air-space-ground network. Background Technology

[0002] As wireless communication evolves towards 6G and integrated space-air-ground networks, the demands on transmission rates, coverage, and reliability of communication systems have increased significantly. Space-based satellite networks need to achieve ubiquitous global connectivity, while airborne drones and high-altitude platforms need to provide flexible coverage enhancement. Ground-based technologies such as massive MIMO (Multiple-Input Multiple-Output) and smart metasurfaces all need to support high-density service access. Multipath fading, as the most critical distortion phenomenon in wireless signal propagation, directly restricts the communication quality and service stability of integrated space-air-ground networks.

[0003] In wireless channels, multipath fading arises from the fact that signals, after being reflected, refracted, and scattered by obstacles, form multiple propagation paths. Signals from different paths superimpose at the receiver, causing random fluctuations in the signal envelope, phase, and amplitude. Depending on the propagation environment and signal characteristics, multipath fading exhibits diverse types, including flat fading, frequency-selective fading, and shadowing fading. Furthermore, integrated air-space-ground networks involve cross-layer communication across space, air, and ground, and also experience unique fading effects such as ionospheric dispersion and tropospheric delay, further complicating channel characteristics.

[0004] Existing technologies for assessing the impact of multipath fading on communication systems mainly employ two methods: one is the sinusoidal superposition method, which constructs a fading model based on the superposition of an infinite number of weighted sine waves. Through discretization, it approximates theoretical characteristics with finite harmonics, achieving high-precision simulation under specific Doppler power spectrum scenarios with low resource consumption. The other is the noise filtering method, which converts a Gaussian random sequence into a fading sequence using inverse discrete Fourier transform, supporting simulation of arbitrary Doppler power spectra. However, it relies on a long filter impulse response, leading to a significant increase in processor resource consumption during hardware implementation. Both methods have significant limitations: the sinusoidal superposition method requires truncation because an infinite number of sine waves cannot be physically realized; when the number of harmonics is small, the actual autocorrelation function deviates significantly from the theoretical value, and it is difficult to adapt to non-classical fading scenarios such as ionospheric and tropospheric fading. While the noise filtering method has strong spectral adaptability, in scenarios with high real-time requirements in integrated air-space-ground networks, the delay caused by the long impulse response reduces the simulation's real-time performance.

[0005] Furthermore, existing multipath fading simulation methods are mostly designed for single scenarios and cannot be applied to multipath fading simulation of space-based, air-based, and ground-based multi-sub-networks, making it difficult to support link-level testing across sub-networks. On the other hand, existing multipath fading simulation methods do not adequately cover special fading effects. For example, shadow fading simulation does not adapt to the dynamic switching of shadow intensity under rapid movement of air-based nodes, resulting in a large deviation between the simulation results and the actual air-space-ground channel characteristics.

[0006] Therefore, it is necessary to provide a new technical solution to improve one or more of the problems existing in the above solutions.

[0007] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0008] The purpose of this disclosure is to provide a multipath fading simulation method based on an integrated air-space-ground network for multipath fading simulation in multiple scenarios, while balancing simulation accuracy and real-time performance.

[0009] According to a first aspect of the present disclosure, a multipath fading simulation method based on an integrated air-space-ground network is provided, comprising: A flat fading channel is constructed based on the sinusoidal superposition method, and the stochastic process of the flat fading channel is optimized. The flat fading channel includes Rayleigh fading channel and Rice fading channel. Configure the basic fading model and scenario simulation sub-network corresponding to the target link according to the target link type and the flat fading channel; the target link type includes space-based link, air-based link or ground-based link, and the scenario simulation sub-network includes ionospheric dispersion simulation unit, tropospheric delay simulation unit and shadow fading simulation unit. Based on the configured basic fading model and the scenario simulation sub-network, multipath fading simulation is performed on the target link to generate multipath fading simulation results.

[0010] In an exemplary embodiment of this disclosure, the construction of a flat fading channel based on the sinusoidal superposition method includes: Superimposing N weighted sine waves yields a functional representation of the stochastic process: (1) in, Let c represent the i-th real Gaussian random process. i,n f represents the Doppler coefficient. i,n θ represents the discrete Doppler frequency. i,n Indicates Doppler phase, The time variable is represented by N, the sine wave number is represented by n, and the sine wave index is represented by n. The Rayleigh fading channel is constructed based on the functional representation of a stochastic process: (2) in, The complex baseband representation of a Rayleigh fading channel. express The real part, express The imaginary part, Indicates the imaginary part. This represents the Doppler coefficient corresponding to the real part. This represents the discrete Doppler frequency corresponding to the real part. N1 represents the Doppler phase corresponding to the real part, and N1 represents the sine wave number corresponding to the real part. This represents the Doppler coefficient corresponding to the imaginary part. This represents the discrete Doppler frequency corresponding to the imaginary part. N represents the Doppler phase corresponding to the imaginary part, N2 represents the sine wave number corresponding to the imaginary part, and f 1,n ≠f 2,n .

[0011] In an exemplary embodiment of this disclosure, optimizing the random process of the flat fading channel includes: The autocorrelation function of a stochastic process in a flat fading channel is represented using the superposition method: (3) in, Represents the autocorrelation function. Indicates average power. Indicates the maximum Doppler frequency shift. Indicates time interval, Represents the zeroth-order Bessel function of the first kind; The autocorrelation function of the stochastic process is truncated to obtain the optimized discrete Doppler frequency and Doppler coefficients; (4) in, This represents the optimized discrete Doppler frequency. This represents the optimized Doppler coefficients. Indicates the number of harmonics.

[0012] In an exemplary embodiment of this disclosure, the step of superimposing N weighted sine waves to obtain a functional representation of a stochastic process further includes: The Doppler coefficients and discrete Doppler frequency in the functional representation of the random process are set as deterministic variables, and the Doppler phase is set as a random variable to adapt to a single Rayleigh fading channel; Alternatively, the Doppler coefficients in the functional representation of the random process can be set as deterministic variables, and the discrete Doppler frequency and Doppler phase can be set as random variables to adapt to multiple Rayleigh fading channels.

[0013] In an exemplary embodiment of this disclosure, the construction of a flat fading channel based on the sinusoidal superposition method further includes: The Rayleigh fading channel is superimposed with the direct path power parameter to construct the Rice fading channel.

[0014] In an exemplary embodiment of this disclosure, configuring the basic fading model and scenario simulation sub-network corresponding to the target link according to the target link type and the flat fading channel includes: When the target link type is a space-based link, the basic fading model of the target link is configured as a frequency-selective fading model, and the ionospheric dispersion simulation unit and the tropospheric delay simulation unit of the scenario simulation sub-network are configured. The frequency-selective fading model includes multiple flat fading channels, each of which corresponds to a multipath component.

[0015] In an exemplary embodiment of this disclosure, configuring the basic fading model and scenario simulation sub-network corresponding to the target link according to the target link type and the flat fading channel includes: When the target link type is an empty-based link, the basic fading model of the target link is configured as a flat Rayleigh fading model, and the shadow fading simulation unit of the scenario simulation sub-network is configured. The flat Rayleigh fading model is constructed based on the Rayleigh fading channel.

[0016] In an exemplary embodiment of this disclosure, configuring the basic fading model and scenario simulation sub-network corresponding to the target link according to the target link type and the flat fading channel includes: When the target link type is a ground-based link, the basic fading model of the target link is configured as a frequency-selective fading model; The frequency-selective fading model includes multiple flat fading channels, each of which corresponds to a multipath component.

[0017] In an exemplary embodiment of this disclosure, the basic fading model of the configured target link is a frequency-selective fading model, including: If a line-of-sight component exists under the target link, the flat fading channel of the frequency selective fading model is a Ricean fading channel; If there is no line-of-sight component under the target link, the flat fading channel of the frequency selective fading model is a Rayleigh fading channel.

[0018] According to a second aspect of the present disclosure, a multipath fading simulation system based on an integrated air-space-ground network is provided, applied to the multipath fading simulation method based on an integrated air-space-ground network as described in any of the preceding claims, the system comprising: A construction module is used to construct a flat fading channel based on the sinusoidal superposition method and optimize the stochastic process of the flat fading channel, which includes Rayleigh fading channels and Rice fading channels. The configuration module is used to configure the basic fading model and scenario simulation sub-network corresponding to the target link according to the target link type and the flat fading channel; the target link type includes space-based link, air-based link or ground-based link, and the scenario simulation sub-network includes ionospheric dispersion simulation unit, tropospheric delay simulation unit and shadow fading simulation unit. The processing module performs multipath fading simulation on the target link based on the configured basic fading model and the scenario simulation sub-network, and generates multipath fading simulation results.

[0019] The technical solution provided in this disclosure may include the following beneficial effects: In the embodiments of this disclosure, a flat fading channel is constructed based on the sinusoidal superposition method as the basic framework, which can save computational resources. At the same time, Rayleigh fading and Rice fading are incorporated into the flat fading channel. Based on the construction of the flat fading channel, the basic fading model and scenario simulation sub-network corresponding to the target link are configured according to the target link type. Different basic fading models, ionospheric dispersion simulation units, tropospheric delay simulation units, and shadow fading simulation units can be switched through configuration, so that it is applicable to space-based, air-based, and ground-based multipath fading simulation, which solves the scenario adaptation limitations of traditional methods and balances simulation accuracy and real-time performance.

[0020] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0021] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure. It is obvious that the drawings described below are merely some embodiments of this disclosure, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0022] Figure 1 A flowchart illustrating a multipath fading simulation method based on an integrated air-space-ground network in an exemplary embodiment of this disclosure is shown. Figure 2 This diagram illustrates the construction of a flat fading channel based on the sinusoidal superposition method in an exemplary embodiment of this disclosure. Figure 3 The diagram illustrates simulation data of the actual autocorrelation function and the theoretical autocorrelation function in an exemplary embodiment of this disclosure. Figure 4 A schematic diagram illustrating a stochastic process simulation of Ricean fading in an exemplary embodiment of this disclosure is shown; Figure 5 A schematic diagram illustrating a Rayleigh fading channel simulation in an exemplary embodiment of this disclosure is shown; Figure 6 A schematic diagram illustrating the Rayleigh fading amplitude and Doppler spectrum in an exemplary embodiment of this disclosure; Figure 7 This diagram illustrates the generation of multiplicative factors in an exemplary embodiment of this disclosure. Figure 8 A schematic diagram of a multipath fading simulation system based on an integrated air-space-ground network in an exemplary embodiment of this disclosure is shown. Detailed Implementation

[0023] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that this disclosure will be more comprehensive and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0024] Furthermore, the accompanying drawings are merely illustrative of this disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0025] This example implementation first provides a multipath fading simulation method based on an integrated air-space-ground network, referencing... Figure 1 As shown, the method may include steps S101 to S104.

[0026] Step S101: Construct a flat fading channel based on the sinusoidal superposition method. The flat fading channel includes Rayleigh fading channel and Rice fading channel.

[0027] It should be explained that flat fading channels include Rayleigh fading channels and Rice fading channels, and the random process of flat fading channels is optimized. Rice fading channels can be constructed based on Rayleigh fading channels.

[0028] Step S102: Configure the basic fading model and scenario simulation sub-network corresponding to the target link according to the target link type and the flat fading channel; the target link type includes space-based link, air-based link or ground-based link, and the scenario simulation sub-network includes ionospheric dispersion simulation unit, tropospheric delay simulation unit and shadow fading simulation unit.

[0029] Step S103: Use the configured basic fading model and the scenario simulation sub-network to perform multipath fading simulation on the target link and generate multipath fading simulation results.

[0030] In the embodiments of this disclosure, a flat fading channel is constructed based on the sinusoidal superposition method as the basic framework, which can save computational resources. At the same time, Rayleigh fading and Rice fading are incorporated into the flat fading channel. Based on the construction of the flat fading channel, the basic fading model and scenario simulation sub-network corresponding to the target link are configured according to the target link type. Different basic fading models, ionospheric dispersion simulation units, tropospheric delay simulation units, and shadow fading simulation units can be switched through configuration, so that it is applicable to space-based, air-based, and ground-based multipath fading simulation, which solves the scenario adaptation limitations of traditional methods and balances simulation accuracy and real-time performance.

[0031] The steps of the method described above in this example implementation will now be explained in more detail.

[0032] The flat fading channel in step S101 is crucial for multipath fading simulation. For a flat fading channel, it is assumed that the plane waves of the multipath components arrive indistinguishably within one symbol period, forming an independent path. Since the core difference between Ricean fading and Rayleigh fading lies in whether the multipath components include line-of-sight components, the Ricean fading channel can be constructed based on the Rayleigh fading channel. From this perspective, the complexity of constructing the flat fading channel in step S101 of this application is greatly reduced. Furthermore, a frequency-selective fading channel consists of multiple distinguishable independent paths; each distinguishable independent path is a flat fading channel. Therefore, the flat fading channel constructed based on step S101 can be flexibly configured with a frequency-selective fading model or a flat Rayleigh fading model adapted to the target link.

[0033] In one embodiment, in step S101, as follows Figure 2 As shown, the construction of a flat fading channel based on the sinusoidal superposition method includes the following steps: Step S1011: Superimpose N weighted sine waves to obtain a functional representation for describing the random process of the channel: (1) in, Let c represent the i-th real Gaussian random process. i,n f represents the Doppler coefficient. i,n θ represents the discrete Doppler frequency. i,n Indicates Doppler phase, The time variable is represented by N, the sine wave number is represented by n, and the sine wave index is represented by n. Step S1012: Construct the Rayleigh fading channel based on the functional representation of the random process: (2) in, The complex baseband representation of a Rayleigh fading channel. express The real part, express The imaginary part, Indicates the imaginary part. This represents the Doppler coefficient corresponding to the real part. This represents the discrete Doppler frequency corresponding to the real part. N1 represents the Doppler phase corresponding to the real part, and N1 represents the sine wave number corresponding to the real part. This represents the Doppler coefficient corresponding to the imaginary part. This represents the discrete Doppler frequency corresponding to the imaginary part. N represents the Doppler phase corresponding to the imaginary part, N2 represents the sine wave number corresponding to the imaginary part, and f 1,n ≠f 2,n .

[0034] It should be noted that, and The cross-correlation function is: (5) in, Let T represent the cross-correlation function, and let T represent half the length of the integration interval. This represents the complex conjugate of the random process μ1(t) at time t. Let represent the value of the random process μ^2(t+τ) at time (t+τ). This indicates a time interval. Therefore, and The necessary and sufficient condition for being irrelevant is f 1,n ≠f 2,n We can choose N2 = N1 + 1 to ensure and They are unrelated.

[0035] In the above embodiments, N weighted sine waves are superimposed to obtain a function representation of the stochastic process. This is an improvement over the traditional method of constructing a fading model based on the superposition of infinitely many weighted sine waves. This improvement can solve the problem that infinite sine waves cannot be used.

[0036] Furthermore, the optimization of the stochastic process of the flat fading channel includes the following steps: Step S1011M: ​​Represent the autocorrelation function of the stochastic process in a flat fading channel using the superposition method: (3) in, Represents the autocorrelation function. Indicates average power. Indicates the maximum Doppler frequency shift. Indicates time interval, Represents the zeroth-order Bessel function of the first kind; Step S1011N: The autocorrelation function of the stochastic process is truncated, specifically the Bessel function of the stochastic process is truncated to obtain the optimized discrete Doppler frequency and Doppler coefficients. (4) in, This represents the optimized discrete Doppler frequency. This represents the optimized Doppler coefficients. Indicates the number of harmonics.

[0037] In the above embodiments, by improving the discrete Doppler frequency and Doppler coefficients, the actual autocorrelation function gradually approaches the theoretical value as the number of harmonics increases, effectively improving the simulation accuracy in non-specific Doppler power spectrum scenarios. Especially in N... i High accuracy can be achieved with a value of ≥8, and the chip resource consumption is only 70% of that of traditional noise filtering methods, making it a perfect fit for miniaturized space-based devices.

[0038] It needs to be explained that in step S1011N, the Bessel function of the random process is truncated by a finite number of steps. The zeroth-order Bessel function of the first kind is commonly used in wireless channel modeling to describe time correlation in mobile environments; its function value varies with 2πf. max The increase in τ and the oscillation attenuation reflect the statistical law of the change of the received signal envelope with time interval τ.

[0039] like Figure 3 As shown, at different harmonic numbers N i Below, simulation data of the actual autocorrelation function and the theoretical autocorrelation function show that: as the number of harmonics N... i As the value increases, the actual autocorrelation function gets closer and closer to the theoretical value.

[0040] Furthermore, the step of superimposing N weighted sine waves to obtain a functional representation of the stochastic process also includes the following steps: The Doppler coefficients and discrete Doppler frequency in the functional representation of the random process are set as deterministic variables, and the Doppler phase is set as a random variable to adapt to a single Rayleigh fading channel; Alternatively, the Doppler coefficients in the functional representation of the random process can be set as deterministic variables, and the discrete Doppler frequency and Doppler phase can be set as random variables to adapt to multiple Rayleigh fading channels.

[0041] In the above embodiments, the functional representation of the random process is designed to adapt to the simulation of a single Rayleigh fading channel and multiple independent Rayleigh fading channels in multipath fading simulation, thereby satisfying the multipath fading simulation of different link types such as space-based, air-based, and ground-based systems.

[0042] Optionally, the Doppler coefficients, discrete Doppler frequency, and Doppler phase in the functional representation of the stochastic process can be set as random variables to adapt to multiple Rayleigh fading channels.

[0043] It should be noted that setting the Doppler coefficients, discrete Doppler frequency, and Doppler phase as random variables is suitable for periods with sufficiently long durations and a sufficiently large number of weighted sine waves. However, considering that the number N of weighted sine waves in this application is limited, setting the Doppler coefficients, discrete Doppler frequency, and Doppler phase as random variables is only an optional approach.

[0044] Furthermore, the method of constructing a flat fading channel based on sinusoidal superposition also includes: The Rayleigh fading channel is superimposed with the direct path power parameter to construct the Rice fading channel.

[0045] It's important to explain that the difference between Ricean fading channels and Rayleigh fading channels lies in the following: when the received signal in the link lacks a dominant static direct signal component, a flat fading channel is a Rayleigh fading channel; otherwise, it's a Ricean fading channel. For example... Figure 4 As shown, since Ricean fading has a direct signal component, the direct path power parameter ρ can be superimposed on the Rayleigh fading stochastic process to realize the stochastic process simulation of Ricean fading without reconstructing the core computing unit, thus saving resources.

[0046] In one embodiment, based on the actual link configuration, when the flat fading channel is a Rayleigh fading channel, the corresponding parameters can be configured as follows: Maximum Doppler frequency shift f max The Hz frequency is 100Hz, the sampling frequency is 600Hz, and the simulation time is 12s; set the parameters. With a value of 0.5 and a terminal speed of 60 km / h, under these parameter settings, Figure 5 Figure 6 This illustrates how Rayleigh fading burden varies with distance. Figure 5 This demonstrates the variation of the normalized amplitude of the complex baseband signal in a Rayleigh fading channel with transmission distance under the above parameter configuration. Figure 6 Verifying the modeling accuracy using the Rayleigh fading amplitude probability density function (PDF) and Rayleigh fading Doppler power spectral density (PSD) from statistical and frequency domain characteristics, respectively, is the core basis for judging whether the channel model conforms to the theory.

[0047] In one embodiment, step S102, configuring the basic fading model and scenario simulation sub-network corresponding to the target link according to the target link type and the flat fading channel, includes: When the target link type is a space-based link, the basic fading model of the target link is configured as a frequency-selective fading model, and the ionospheric dispersion simulation unit and the tropospheric delay simulation unit of the scenario simulation sub-network are configured.

[0048] The frequency-selective fading model includes multiple flat fading channels, each of which corresponds to a multipath component.

[0049] Optionally, when the target link type is a space-based link, the frequency-selective fading model has two flat fading channels or three flat fading channels.

[0050] It should be explained that, in the case of a space-based link, in order to solve the problem of transmission signal distortion caused by ionospheric group delay dispersion and tropospheric delay, it is necessary to configure an ionospheric dispersion simulation unit and a tropospheric delay simulation unit.

[0051] The ionospheric dispersion simulation unit is used to establish the correlation between total electron content and group delay and phase delay. Then, by designing a filter that approximates the characteristics of group delay and phase delay, the host computer can set the value of total electron content according to the test requirements. The filter parameters are generated by the host computer in real time and transmitted to the chip to ensure that the simulation results can accurately reflect the dispersion effect under different ionospheric states.

[0052] In the tropospheric delay simulation unit, the tropospheric delay can be divided into dry delay and wet delay based on the Hopfield model. The dry delay is determined by atmospheric pressure and temperature, while the wet delay is determined by water vapor partial pressure and temperature. By inputting ground meteorological parameters and altitude into the model, the tropospheric delay values ​​at different locations can be accurately calculated to meet the accuracy requirements of tropospheric delay simulation and ensure consistency between multipath fading simulation results and real channels. The Hopfield model is a classic empirical calculation model for tropospheric delay, widely used in satellite navigation and positioning and wireless channel modeling. This model divides the path delay generated when a signal passes through the troposphere into two independent components: dry delay (static delay) and wet delay (non-static delay), which are estimated based on surface meteorological parameters and altitude, respectively. The dry delay component is mainly caused by atmospheric static effects and depends on surface atmospheric pressure and temperature; the wet delay component is determined by the water vapor content in the atmosphere and depends on surface water vapor partial pressure and temperature. By integrating the refractive index of each atmospheric layer along the signal propagation path, the model establishes a functional relationship between the total tropospheric delay from the ground to the zenith and ground meteorological observations. In this application, the Hopfield model can be used to calculate and inject tropospheric delay in real time based on actual or set ground meteorological parameters and the altitude of link nodes, thereby accurately reproducing the tropospheric delay effect under different geographical locations and meteorological conditions, and ensuring a high degree of consistency between the air-ground multipath fading simulation results and the real propagation environment.

[0053] In one embodiment, step S102, configuring the basic fading model and scenario simulation sub-network corresponding to the target link according to the target link type and the flat fading channel, includes: When the target link type is an empty-based link, the basic fading model of the target link is configured as a flat Rayleigh fading model, and the shadow fading simulation unit of the scenario simulation sub-network is configured. The flat Rayleigh fading model is constructed based on the Rayleigh fading channel, as detailed in steps S1011-S1012.

[0054] It should be explained that shadow fading is caused by occlusion from ground obstacles, as in this application, such as Figure 7 As shown, the shadow fading simulation unit uses a log-normal model to generate multiplicative factors that follow a log-normal distribution. , The multiplicative factor representing shadow fading. This represents the exponential operation with base e as the natural constant, where the exponent μ follows a normal distribution. Let represent a random variable that follows a normal distribution. Its mean and variance are determined by the target shadow fading environment, typically... , where x ~ N(0,1).

[0055] Optionally, when configuring the shadow fading simulation unit, the Doppler frequency shift can be set to 100Hz and the sampling frequency to 600Hz to adapt to the fast time-varying characteristics.

[0056] Optionally, when configuring the shadow fading simulation unit, the colored Gaussian noise power spectrum can be set to the Gaussian power spectrum to suit the shadow fading simulation requirements.

[0057] It should be noted that when the target link type is an airborne link, the number of harmonics N is configured. i ≥8. For example, the parameter configuration is as follows: N i =8, maximum Doppler frequency shift is 100Hz, sampling frequency is 600Hz, simulation points Ns=7200, simulation time is 12s. Based on this configuration, the variation of shadow fading amplitude with distance can be simulated. The fitted shadow fading probability density function is in high agreement with the theoretical curve of the log-normal distribution, thus solving the dynamic switching adaptation problem.

[0058] It should also be noted that by setting three different sets of parameter configurations, mild shadow decay, moderate shadow decay, and severe shadow decay can be simulated respectively, so as to achieve dynamic switching and adaptation of shadow intensity.

[0059] In the shadow fading simulation unit, the multiplicative factor logarithmic mean and standard deviation These two parameters determine the fading intensity, and dynamic switching between different shading levels can be achieved by adjusting them. Typical configurations for the three sets of parameters are shown in Table 1 below: Table 1 Parameter Configuration In one embodiment, step S102, configuring the basic fading model and scenario simulation sub-network corresponding to the target link according to the target link type and the flat fading channel, includes: When the target link type is a ground-based link, the basic fading model of the target link is configured as a frequency-selective fading model; The frequency-selective fading model includes multiple flat fading channels, each of which corresponds to a multipath component.

[0060] It should be noted that when the target link type is a ground-based link, the frequency-selective fading model has less than or equal to six flat fading channels.

[0061] Optionally, in step S102, the frequency selective fading model can adopt a discrete tap delay line structure, and the delay and amplitude of each flat fading channel can be set as independently adjustable parameters; the frequency selective fading model supports 6 multipath components, which fully meets the requirements of 2-3 components for space-based links and a maximum of 6 components for ground-based links.

[0062] Optionally, in step S102, for the configuration of the frequency selective fading model, the relative intensity adjustment range of the multipath component is set to 0~30dB, and the adjustment step is reduced to 0.5dB. This can more finely simulate the intensity difference of the multipath component under different scenarios, and improve the simulation accuracy by more than double compared with traditional simulators.

[0063] In one embodiment, the basic fading model of the configured target link is a frequency-selective fading model, including: If a line-of-sight component exists under the target link, the flat fading channel of the frequency-selective fading model is a Ricean fading channel.

[0064] If there is no line-of-sight component under the target link, the flat fading channel of the frequency selective fading model is a Rayleigh fading channel.

[0065] The flat fading channel constructed through step S101 of this application can be flexibly configured to adapt to the target link, regardless of whether there is a line-of-sight component under the target link.

[0066] In one embodiment, in step S103, the current configuration layer of the basic fading model and the scenario simulation sub-network configured in step S102 is obtained.

[0067] For example, in the case of a space-based link, the configured frequency-selective fading model, ionospheric dispersion simulation unit, and tropospheric delay simulation unit are obtained. For instance, the frequency-selective fading model is configured as follows: Space-based links (such as those from low-Earth orbit satellites to ground terminals) typically include a strong direct path (path 1 in Table 2) and 1-2 secondary multipath components reflected by the ionosphere or scattered by the ground (paths 2 and 3 in Table 2). Typical frequency-selective fading model parameter configurations are shown in Table 2 below: Table 2 Parameter Configuration for Frequency Selective Fading Model For example, in the case of an empty-base link, obtain the configured flat Rayleigh fading model and the configured shadowed fading simulation unit. For instance, configure the number of harmonics N. i =8, maximum Doppler frequency shift is 100Hz, sampling frequency is 600Hz, Doppler spectrum type is Jakesi spectrum, average power is Normalized to 0.5 (real part) / 0.5 (imaginary part), the number of simulation points Ns = 7200, and the simulation time is 12s. Based on this configuration, the variation of shadow fading amplitude with distance can be simulated. The fitted shadow fading probability density function is in high agreement with the theoretical curve of the log-normal distribution, thus solving the dynamic switching adaptation problem.

[0068] For example, in the case of a ground-based link, a pre-configured frequency-selective fading model is obtained. Ground-based links (such as those between a terrestrial base station and a mobile terminal or vehicle-to-everything (V2X) communication) are typically located in urban or suburban environments. Signals are reflected and scattered by buildings, forming multiple distinguishable propagation paths, necessitating a frequency-selective fading model. This model employs a discrete-tap delay line structure, where each tap corresponds to an independent multipath component, and each multipath component is implemented by a flat fading channel. Typical parameter configurations are shown in Table 3 below. Table 3 Parameter Configuration For example, in step S103, when the target link is a space-based link, multipath fading simulation is performed on the space-based link based on the configured frequency-selective fading model, the ionospheric dispersion simulation unit, and the tropospheric delay simulation unit; when the target link is a space-based link, multipath fading simulation is performed on the space-based link based on the configured flat Rayleigh fading model and the shadow fading simulation unit; when the target link is a ground-based link, multipath fading simulation is performed on the ground-based link based on the configured frequency-selective fading model.

[0069] It should be explained that the multipath fading simulation of the target link using the configured basic fading model and scenario simulation subnetwork in step S103 can be described as follows: Based on the basic fading model and scenario simulation subnetwork, determine the relative time delay and Doppler frequency shift of each multipath component under the target link, and generate a time-varying fading sequence corresponding to each multipath component; perform frequency shift processing and time delay alignment processing on the time-varying fading sequence according to the relative time delay and Doppler frequency shift to obtain the signals of each multipath component; perform convolution operation between the processed multipath component signals and the transmitted signal to obtain the multipath fading simulation result. The above-described logical algorithm for multipath fading simulation of the target link using the basic fading model and scenario simulation subnetwork is a conventional technique in this field, and will not be described in detail here.

[0070] This embodiment also provides a multipath fading simulation system based on an integrated air-space-ground network, including a construction module, a configuration module, and a processing module.

[0071] A construction module is used to construct a flat fading channel based on the sinusoidal superposition method and optimize the stochastic process of the flat fading channel, which includes Rayleigh fading channels and Rice fading channels.

[0072] The configuration module is used to configure the basic fading model and scenario simulation sub-network corresponding to the target link according to the target link type and the flat fading channel; the target link type includes space-based link, air-based link or ground-based link, and the scenario simulation sub-network includes ionospheric dispersion simulation unit, tropospheric delay simulation unit and shadow fading simulation unit.

[0073] The processing module uses the configured basic fading model and the scenario simulation sub-network to perform multipath fading simulation on the target link and generate multipath fading simulation results.

[0074] In the embodiments of this disclosure, a flat fading channel is constructed based on the sinusoidal superposition method using a construction module, which saves computational resources. Rayleigh fading and Rice fading are incorporated into the flat fading channel. Based on the construction of the flat fading channel, a configuration module configures the basic fading model and scenario simulation sub-network corresponding to the target link according to the target link type. Different basic fading models, ionospheric dispersion simulation units, tropospheric delay simulation units, and shadow fading simulation units can be switched through configuration, thereby dynamically adapting to space-based, air-based, and ground-based multipath fading simulations and obtaining multipath fading simulation results. This solves the scenario adaptation limitations of traditional methods and balances simulation accuracy and real-time performance.

[0075] Regarding the system in the above embodiments, the specific manner in which each unit performs operations has been described in detail in the embodiments related to the method, and will not be elaborated here.

[0076] It should be noted that although several units of the system for executing actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more units described above can be embodied in one unit. Conversely, the features and functions of one unit described above can be further divided and embodied by multiple units. Some or all of the units can be selected to achieve the purpose of this disclosure according to actual needs. Those skilled in the art can understand and implement this without any inventive effort.

[0077] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the appended claims.

Claims

1. A multipath fading simulation method based on an integrated air-space-ground network, characterized in that, include: A flat fading channel is constructed based on the sinusoidal superposition method, and the stochastic process of the flat fading channel is optimized. The flat fading channel includes Rayleigh fading channel and Rice fading channel. Configure the basic fading model and scenario simulation sub-network corresponding to the target link according to the target link type and the flat fading channel; the target link type includes space-based link, air-based link or ground-based link, and the scenario simulation sub-network includes ionospheric dispersion simulation unit, tropospheric delay simulation unit and shadow fading simulation unit. The configured basic fading model and the scenario simulation sub-network are used to perform multipath fading simulation on the target link, generating multipath fading simulation results.

2. The multipath fading simulation method based on an integrated air-space-ground network according to claim 1, characterized in that, The method for constructing a flat fading channel based on sinusoidal superposition includes: Superimposing N weighted sine waves yields a functional representation of the stochastic process: （1） in, Let c represent the i-th real Gaussian random process. i,n f represents the Doppler coefficient. i,n θ represents the discrete Doppler frequency. i,n Indicates Doppler phase, The time variable is represented by N, the sine wave number is represented by n, and the sine wave index is represented by n. The Rayleigh fading channel is constructed based on the functional representation of a stochastic process: （2） in, The complex baseband representation of a Rayleigh fading channel. express The real part, express The imaginary part, Indicates the imaginary part. This represents the Doppler coefficient corresponding to the real part. This represents the discrete Doppler frequency corresponding to the real part. N represents the Doppler phase corresponding to the real part, and N1 represents the sine wave number corresponding to the real part. This represents the Doppler coefficient corresponding to the imaginary part. This represents the discrete Doppler frequency corresponding to the imaginary part. N represents the Doppler phase corresponding to the imaginary part, N2 represents the sine wave number corresponding to the imaginary part, and f 1,n ≠f 2,n .

3. The multipath fading simulation method based on an integrated air-space-ground network according to claim 1 or 2, characterized in that, The optimization of the stochastic process of the flat fading channel includes: The autocorrelation function of a stochastic process in a flat fading channel is represented using the superposition method: （3） in, Represents the autocorrelation function. Indicates average power. Indicates the maximum Doppler frequency shift. Indicates time interval, Represents the zeroth-order Bessel function of the first kind; The autocorrelation function of the stochastic process is truncated to obtain the optimized discrete Doppler frequency and Doppler coefficients; （4） in, This represents the optimized discrete Doppler frequency. This represents the optimized Doppler coefficient. Indicates the number of harmonics.

4. The multipath fading simulation method based on an integrated air-space-ground network according to claim 2, characterized in that, The step of superimposing N weighted sine waves to obtain a functional representation of a stochastic process further includes: The Doppler coefficients and discrete Doppler frequency in the functional representation of the random process are set as deterministic variables, and the Doppler phase is set as a random variable to adapt to a single Rayleigh fading channel; Alternatively, the Doppler coefficients in the functional representation of the random process can be set as deterministic variables, and the discrete Doppler frequency and Doppler phase can be set as random variables to adapt to multiple Rayleigh fading channels.

5. The multipath fading simulation method based on an integrated air-space-ground network according to claim 2, characterized in that, The method for constructing a flat fading channel based on sinusoidal superposition also includes: The Rayleigh fading channel is superimposed with the direct path power parameter to construct the Rice fading channel.

6. The multipath fading simulation method based on an integrated air-space-ground network according to claim 1, characterized in that, The step of configuring the basic fading model and scenario simulation sub-network corresponding to the target link based on the target link type and the flat fading channel includes: When the target link type is a space-based link, the basic fading model of the target link is configured as a frequency-selective fading model, and the ionospheric dispersion simulation unit and the tropospheric delay simulation unit of the scenario simulation sub-network are configured. The frequency-selective fading model includes multiple flat fading channels, each of which corresponds to a multipath component.

7. The multipath fading simulation method based on an integrated air-space-ground network according to claim 1, characterized in that, The step of configuring the basic fading model and scenario simulation sub-network corresponding to the target link based on the target link type and the flat fading channel includes: When the target link type is an empty-based link, the basic fading model of the target link is configured as a flat Rayleigh fading model, and the shadow fading simulation unit of the scenario simulation sub-network is configured. The flat Rayleigh fading model is constructed based on the Rayleigh fading channel.

8. The multipath fading simulation method based on an integrated air-space-ground network according to claim 1, characterized in that, The step of configuring the basic fading model and scenario simulation sub-network corresponding to the target link based on the target link type and the flat fading channel includes: When the target link type is a ground-based link, the basic fading model of the target link is configured as a frequency-selective fading model; The frequency-selective fading model includes multiple flat fading channels, each of which corresponds to a multipath component.

9. The multipath fading simulation method based on an integrated air-space-ground network according to any one of claims 6 or 8, characterized in that, The basic fading model for the target link configuration is a frequency-selective fading model, including: If a line-of-sight component exists under the target link, the flat fading channel of the frequency selective fading model is a Ricean fading channel; If there is no line-of-sight component under the target link, the flat fading channel of the frequency selective fading model is a Rayleigh fading channel.

10. A multipath fading simulation system based on an integrated air-space-ground network, characterized in that, The system, applied to the multipath fading simulation method based on an integrated air-space-ground network as described in any one of claims 1 to 9, comprises: A construction module is used to construct a flat fading channel based on the sinusoidal superposition method and optimize the stochastic process of the flat fading channel, which includes Rayleigh fading channels and Rice fading channels. The configuration module is used to configure the basic fading model and scenario simulation sub-network corresponding to the target link according to the target link type and the flat fading channel; the target link type includes space-based link, air-based link or ground-based link, and the scenario simulation sub-network includes ionospheric dispersion simulation unit, tropospheric delay simulation unit and shadow fading simulation unit. The processing module uses the configured basic fading model and the scenario simulation sub-network to perform multipath fading simulation on the target link and generate multipath fading simulation results.

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