Non-Gaussian channel modeling method and device based on ball invariant process
By using a non-Gaussian channel modeling method based on spherically invariant processes, channel sounding data is acquired and a channel impulse response model is constructed. This solves the problem that traditional methods cannot describe the dynamic time-varying behavior of the channel, and achieves higher-precision channel modeling and simulation.
Patent Information
- Application Number
- CN202511412888.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-29
- Publication Date
- 2025-12-12
AI Technical Summary
Traditional channel modeling methods based on spherically invariant random processes cannot accurately describe the dynamic time-varying behavior of signals, especially the phase changes and instantaneous power spectrum characteristics caused by the Doppler effect.
By acquiring channel sounding data, the Doppler power spectral density and channel fading model are calculated. The channel fading model is described using a spherically invariant random process. The amplitude and phase models of the channel impulse response are constructed, and the channel impulse response is generated by combining the Doppler power spectral density.
It improves the simulation accuracy of the channel model, enabling a more accurate description of the dynamic characteristics of the wireless propagation channel and enhancing the simulation and optimization capabilities of wireless systems.
Smart Images
Figure CN121124984A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of wireless communication and channel modeling, and particularly relates to a non-Gaussian channel modeling method and device based on a spherically invariant process. BACKGROUND
[0002] In a wireless communication system, a channel is a physical medium through which a signal propagates from a transmitting end to a receiving end. Due to the influence of various factors such as reflection, diffraction, scattering, multipath, shadow fading and Doppler effect on the wireless signal during transmission, the amplitude, phase and frequency of the signal change, which directly affects the performance of the communication system. Therefore, accurately describing and modeling the behavior of the wireless propagation channel through channel modeling is the basis and premise for the design, simulation and optimization of the wireless communication system.
[0003] Traditional channel modeling methods include channel modeling based on an LP-Norm method and channel modeling based on a spherically invariant random process. However, the channel modeling based on the spherically invariant random process can accurately describe the probability distribution of the signal envelope, but cannot directly capture the dynamic time-varying behavior of the channel impulse response, such as the phase change caused by the Doppler effect or the instantaneous power spectrum characteristics.
[0004] Therefore, there is an urgent need for a solution to solve the above technical problems. SUMMARY
[0005] In view of the defects in the prior art, the present application provides a non-Gaussian channel modeling method and device based on a spherically invariant process.
[0006] To achieve the above-mentioned purpose, the technical solution adopted by the present application is as follows: On the one hand, the present application provides a non-Gaussian channel modeling method based on a spherically invariant process, comprising the following steps: obtaining channel sounding data; obtaining the Doppler power spectral density corresponding to each multipath and a channel fading model based on the channel sounding data; describing the channel fading model with a spherically invariant random process, calculating the envelope of the spherically invariant random process, and calculating the channel impulse response amplitude based on the envelope of the spherically invariant random process; constructing a channel impulse response phase model based on the Doppler power spectral density; constructing a channel impulse response model based on the channel impulse response amplitude and the channel impulse response phase model.
[0007] Further, the Doppler power spectral density corresponding to each multipath is obtained according to the following steps: extracting the multipath parameters in the channel sounding data through the SAGE algorithm; The multipath parameters are statistically processed to obtain a time sequence of the multipath parameters; Based on the time sequence of the multipath parameters, a Doppler power spectral density corresponding to each multipath is obtained.
[0008] Further, the spherically invariant random process is:
[0009] wherein, is a spherically invariant random process; is a non-negative random variable; is a zero-mean Gaussian process.
[0010] Further, an envelope of the spherically invariant random process is calculated according to the following formula:
[0011] wherein, is an envelope of the spherically invariant random process; is a non-negative random variable; is an envelope of a narrowband zero-mean Gaussian process; is an in-phase component of the spherically invariant random process; is a quadrature component of the spherically invariant random process; is an in-phase component of a zero-mean Gaussian process; is a quadrature component of a zero-mean Gaussian process.
[0012] Further, the channel impulse response amplitude is calculated based on the envelope of the spherically invariant random process, comprising: constructing a probability density function of the non-negative random variable and a probability density function of the envelope of the narrowband zero-mean Gaussian process; obtaining a cumulative distribution function corresponding to the probability density function of the non-negative random variable and the probability density function of the envelope of the narrowband zero-mean Gaussian process, respectively; generating a corresponding non-negative random variable and an envelope of the narrowband zero-mean Gaussian process using the cumulative distribution functions; calculating the channel impulse response amplitude based on the generated non-negative random variable and the envelope of the narrowband zero-mean Gaussian process.
[0013] Further, the probability density function of the non-negative random variable is:
[0014] wherein, is a probability density function of a non-negative random variable; L is a proper integral path on a complex plane; i is a complex unit; s is a complex variable of the Mellin transform; represents Merlin transformation; Let be the values of the independent variable of the nonnegative random variable; The probability density function of the envelope of the narrowband zero-mean Gaussian process is:
[0015] in, Let be the probability density function of the envelope of a narrowband zero-mean Gaussian process; Let the independent variable be the value of the envelope of a sphere-invariant random process; H This is the Fox H function.
[0016] Furthermore, the amplitude of the channel impulse response is calculated according to the following formula:
[0017] in, This represents the amplitude of the channel impulse response. It is a non-negative random variable; This is the envelope of a narrowband zero-mean Gaussian process.
[0018] Furthermore, a channel impulse response phase model is constructed based on the Doppler power spectral density, including: The maximum Doppler frequency was obtained based on the Doppler power spectral density. A channel impulse response phase model is constructed based on the maximum Doppler frequency; The channel impulse response phase model is as follows:
[0019] in, The channel impulse response phase; The maximum Doppler frequency; Angle of incidence; For the initial phase, .
[0020] Furthermore, the channel impulse response model is as follows:
[0021] in, This is the channel impulse response; This represents the amplitude of the channel impulse response. It is a non-negative random variable; The envelope of a zero-mean Gaussian process; The imaginary unit; This represents the channel impulse response phase.
[0022] On the other hand, the present invention provides a non-Gaussian channel modeling apparatus based on a sphere-invariant process, comprising: The first module is used to acquire channel sounding data; The second module is used to obtain the Doppler power spectral density and channel fading model for each multipath based on channel sounding data. The third module is used to describe the channel fading model using a sphere-invariant random process, calculate the envelope of the sphere-invariant random process, and calculate the channel impulse response amplitude based on the envelope of the sphere-invariant random process. The fourth module is used to construct a channel impulse response phase model based on Doppler power spectral density; The fifth module is used to construct a channel impulse response model based on the channel impulse response amplitude and the channel impulse response phase model.
[0023] Compared with the prior art, the beneficial technical effects of the present invention are as follows: The present invention provides a non-Gaussian channel modeling method and apparatus based on a spherically invariant process. It obtains the Doppler power spectral density corresponding to each multipath through channel sounding data, and constructs a channel impulse response phase model with the Doppler power spectral density, thereby introducing phase change into the channel fading model. It generates the channel impulse response by driving the Doppler spectrum, thereby reflecting the dynamic characteristics of the channel in the obtained channel impulse response model and improving the simulation accuracy of the channel model.
[0024] This invention can improve the accuracy and realism of channel models, providing a foundation for the simulation and optimization of wireless systems. Attached Figure Description
[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.
[0026] Figure 1 A flowchart of a non-Gaussian channel modeling method based on a sphere-invariant process is provided in one embodiment; Figure 2 A comparison chart of measured data and simulation results provided in one embodiment; Figure 3 A comparison chart of measured data and simulation results for one embodiment of the Doppler power spectral density. Detailed Implementation
[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0028] Reference Figure 1 One embodiment provides a non-Gaussian channel modeling method based on a sphere-invariant process, comprising the following steps: Acquire channel probe data; Based on channel sounding data, obtain the Doppler power spectral density and channel fading model for each multipath path; The channel fading model is described by a sphere-invariant random process, the envelope of the sphere-invariant random process is calculated, and the channel impulse response amplitude is calculated based on the envelope of the sphere-invariant random process. A channel impulse response phase model was constructed based on Doppler power spectral density; A channel impulse response model is constructed based on the channel impulse response amplitude and channel impulse response phase model.
[0029] The Doppler power spectral density corresponding to each multipath is obtained by channel sounding data, and a channel impulse response phase model is constructed using the Doppler power spectral density, thereby introducing phase change into the channel fading model; the channel impulse response is generated by driving the Doppler spectrum, thereby reflecting the dynamic characteristics of the channel in the obtained channel impulse response model and improving the simulation accuracy of the channel model.
[0030] In one embodiment, the Doppler power spectral density corresponding to each multipath is obtained according to the following steps: Multipath parameters are extracted from channel sounding data using the SAGE algorithm; Statistical processing of the multipath parameters yields the time series of the multipath parameters. The Doppler power spectral density corresponding to each multipath is obtained based on the time series of multipath parameters.
[0031] In one embodiment, the ball-invariant random process is as follows:
[0032] in, It is a sphere-invariant random process; It is a non-negative random variable. and They are independent of each other; It is a zero-mean Gaussian process.
[0033] The envelope of the ball-invariant random process is calculated according to the following formula:
[0034] in, Let be the envelope of a sphere-invariant random process; It is a non-negative random variable; The envelope of a narrowband zero-mean Gaussian process. Follows a Rayleigh distribution; For the in-phase components of a spherically invariant random process; These are the orthogonal components of a spherically invariant random process; The in-phase component of a zero-mean Gaussian process; These are the orthogonal components of a zero-mean Gaussian process; For a moment.
[0035] When a nonnegative random variable is treated as an independent variable, a shading effect or heavy-tailed property is introduced. The envelope of a narrowband zero-mean Gaussian process reflects the multipath effect.
[0036] In one embodiment, the nonnegative random variable follows a distribution with heavy-tailed characteristics, thereby fitting a non-Gaussian distribution.
[0037] In a preferred embodiment, calculating the channel impulse response amplitude based on the envelope of a sphere-invariant random process includes: Construct the probability density function of a nonnegative random variable and the probability density function of the envelope of a narrowband zero-mean Gaussian process; Obtain the cumulative distribution functions corresponding to the probability density functions of nonnegative random variables and the probability density functions of the envelope of narrowband zero-mean Gaussian processes, respectively; The cumulative distribution function is used to generate the envelope of the corresponding nonnegative random variable and the narrowband zero-mean Gaussian process; The channel impulse response amplitude is calculated based on the envelope of the generated nonnegative random variables and a narrowband zero-mean Gaussian process.
[0038] By introducing the Fox H function and Merlin transform, a unified analytical framework for non-Gaussian channels is constructed to compute the probability density function, thereby adapting to different types of non-Gaussian channels.
[0039] For functions , Merlin's transformation is:
[0040] in, Let be a complex variable of the Merlin transform.
[0041] Merlin inverse transform is:
[0042] in, c is the real part of the integration path;i It is a complex unit.
[0043] The Fox H function can be expressed by the inverse Merlin transform as follows:
[0044] in, Integer and ; It is the Gamma function; L For a suitable integration path on the complex plane; the parameters satisfy... and ,in For the set of complex numbers, ; in Not limited to primary value; s Let be a complex variable under the Merlin transform; It is the imaginary unit.
[0045] The probability density function of the envelope of the narrowband zero-mean Gaussian process is:
[0046] Since the envelope of a narrowband zero-mean Gaussian process follows a Rayleigh distribution, then: ; Therefore, the probability density function of the envelope of a narrowband zero-mean Gaussian process can be expressed by the Fox H function as follows:
[0047] in, Let be the probability density function of the envelope of a narrowband zero-mean Gaussian process; x Let be the values of the independent variable that enclose the envelope of a spherically invariant random process.
[0048] The probability density function of the nonnegative random variable can be expressed as:
[0049] in, For a nonnegative random variable, the probability density function is used. express Merlin transformation; Let be the values of the independent variable of the nonnegative random variable; For nonnegative random variables ,because and The independence of , according to the definition of Merlin transform, has:
[0050] Then random variable The Merlin transform can be expressed as:
[0051] The envelope of the ball-invariant random process X The distribution needs to be determined based on the specific channel fading model. In this embodiment, the fading model is the Nakagami fading model. X If it follows a Nakagami distribution, then the probability density function of the envelope of a narrowband zero-mean Gaussian process can be obtained. X Merlin's transformation is:
[0052] but:
[0053] Further obtain V The probability density function can be expressed using the Fox H function as follows: ; in, For a nonnegative random variable, the probability density function is used. The fading depth; Average power; Gamma function For Fox H function, Integer and .
[0054] The channel impulse response amplitude is calculated according to the following formula:
[0055] in, This represents the amplitude of the channel impulse response. It is a non-negative random variable; This is the envelope of a narrowband zero-mean Gaussian process.
[0056] A channel impulse response phase model is constructed based on Doppler power spectral density, including: The maximum Doppler frequency was obtained based on the Doppler power spectral density. A channel impulse response phase model is constructed based on the maximum Doppler frequency; The channel impulse response phase model is as follows:
[0057] in, The channel impulse response phase; The maximum Doppler frequency; Angle of incidence; The initial phase is random. .
[0058] The maximum Doppler frequency is obtained by using the Doppler power spectral density, and then the channel impulse response phase model is constructed using the maximum Doppler frequency. This incorporates the dynamic characteristics of the channel into the phase model, enabling the subsequently constructed channel impulse response model to more accurately describe the behavior of the wireless propagation channel.
[0059] The channel impulse response model is as follows:
[0060] in, This is the channel impulse response; This represents the amplitude of the channel impulse response. It is a non-negative random variable; The envelope of a zero-mean Gaussian process; The imaginary unit; This represents the channel impulse response phase.
[0061] To verify the effectiveness of the method described in this invention, measured data and simulation results were compared. The comparison results are as follows: Figure 2 , Figure 3 As shown. (Refer to...) Figure 2 It can be seen that the amplitude distribution (i.e., the simulated curve) of the channel impulse response model obtained by the method described in this invention is basically consistent with the measured data; from Figure 3 It can be seen that the Doppler power spectral density obtained by the method described in this invention is basically consistent with the measured fitting curve, indicating that introducing phase to form a channel impulse response model can reflect the dynamic characteristics of the channel, so that the constructed channel model can more accurately describe the behavior of the wireless propagation channel.
[0062] One embodiment provides a non-Gaussian channel modeling apparatus based on a sphere-invariant process, comprising: The first module is used to acquire channel sounding data; The second module is used to obtain the Doppler power spectral density and channel fading model for each multipath based on channel sounding data. The third module is used to describe the channel fading model using a sphere-invariant random process, calculate the envelope of the sphere-invariant random process, and calculate the channel impulse response amplitude based on the envelope of the sphere-invariant random process. The fourth module is used to construct a channel impulse response phase model based on Doppler power spectral density; The fifth module is used to construct a channel impulse response model based on the channel impulse response amplitude and the channel impulse response phase model.
[0063] Matters not covered in this invention are common knowledge.
[0064] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0065] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these modifications and improvements all fall within the protection scope of this application.
[0066] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.
Claims
1. A non-Gaussian channel modeling method based on spherically invariant processes, characterized in that, Includes the following steps: Acquire channel probe data; Based on channel sounding data, obtain the Doppler power spectral density and channel fading model for each multipath path; The channel fading model is described by a sphere-invariant random process, the envelope of the sphere-invariant random process is calculated, and the channel impulse response amplitude is calculated based on the envelope of the sphere-invariant random process. A channel impulse response phase model is constructed based on Doppler power spectral density; A channel impulse response model is constructed based on the channel impulse response amplitude and channel impulse response phase model.
2. The non-Gaussian channel modeling method based on sphere-invariant processes as described in claim 1, characterized in that, The Doppler power spectral density corresponding to each multipath is obtained according to the following steps: Multipath parameters are extracted from channel sounding data using the SAGE algorithm; Statistical processing of the multipath parameters yields the time series of the multipath parameters. The Doppler power spectral density corresponding to each multipath is obtained based on the time series of multipath parameters.
3. The non-Gaussian channel modeling method based on sphere-invariant processes as described in claim 1, characterized in that, The invariant random process of the ball is as follows: in, It is a sphere-invariant random process; It is a non-negative random variable; It is a zero-mean Gaussian process.
4. The non-Gaussian channel modeling method based on sphere-invariant processes as described in claim 1, characterized in that, The envelope of the ball-invariant random process is calculated according to the following formula: in, Let be the envelope of a sphere-invariant random process; It is a non-negative random variable; The envelope of a narrowband zero-mean Gaussian process; For the in-phase components of a spherically invariant random process; These are the orthogonal components of a spherically invariant random process; The in-phase component of a zero-mean Gaussian process; These are the orthogonal components of a zero-mean Gaussian process.
5. The non-Gaussian channel modeling method based on a sphere-invariant process as described in claim 4, characterized in that, Envelope calculation of channel impulse response amplitude based on spherically invariant random processes includes: Construct the probability density function of a nonnegative random variable and the probability density function of the envelope of a narrowband zero-mean Gaussian process; Obtain the cumulative distribution functions corresponding to the probability density functions of nonnegative random variables and the probability density functions of the envelope of narrowband zero-mean Gaussian processes, respectively; The cumulative distribution function is used to generate the envelope of the corresponding nonnegative random variable and the narrowband zero-mean Gaussian process; The channel impulse response amplitude is calculated based on the envelope of the generated nonnegative random variables and a narrowband zero-mean Gaussian process.
6. The non-Gaussian channel modeling method based on a sphere-invariant process as described in claim 5, characterized in that, The probability density function of the nonnegative random variable is: in, For a nonnegative random variable, the probability density function is used. L For the appropriate integration path on the complex plane; i For complex units; s Let be a complex variable under the Merlin transform; express Merlin transformation; Let be the values of the independent variable of the nonnegative random variable; The probability density function of the envelope of the zero-mean Gaussian process is: in, The probability density function of the envelope of a zero-mean Gaussian process; Let the independent variable be the value of the envelope of a sphere-invariant random process; H This is the Fox H function.
7. The non-Gaussian channel modeling method based on sphere-invariant processes as described in claim 5, characterized in that, The channel impulse response amplitude is calculated according to the following formula: in, This represents the amplitude of the channel impulse response. It is a non-negative random variable; The envelope of a zero-mean Gaussian process.
8. The non-Gaussian channel modeling method based on sphere-invariant processes as described in claim 1, characterized in that, A channel impulse response phase model is constructed based on Doppler power spectral density, including: The maximum Doppler frequency was obtained based on the Doppler power spectral density. A channel impulse response phase model is constructed based on the maximum Doppler frequency; The channel impulse response phase model is as follows: in, The channel impulse response phase; The maximum Doppler frequency; Angle of incidence; For the initial phase, .
9. The non-Gaussian channel modeling method based on sphere-invariant processes as described in claim 1, characterized in that, The channel impulse response model is as follows: in, This is the channel impulse response; This represents the amplitude of the channel impulse response. It is a non-negative random variable; The envelope of a zero-mean Gaussian process; The imaginary unit; This represents the channel impulse response phase.
10. A non-Gaussian channel modeling device based on a spherically invariant process, characterized in that, include: The first module is used to acquire channel sounding data; The second module is used to obtain the Doppler power spectral density and channel fading model for each multipath based on channel sounding data. The third module is used to describe the channel fading model using a sphere-invariant random process, calculate the envelope of the sphere-invariant random process, and calculate the channel impulse response amplitude based on the envelope of the sphere-invariant random process. The fourth module is used to construct a channel impulse response phase model based on Doppler power spectral density; The fifth module is used to construct a channel impulse response model based on the channel impulse response amplitude and the channel impulse response phase model.