CN114268398A - Simulation algorithm of suzuki channel - Google Patents
Simulation algorithm of suzuki channel Download PDFInfo
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- CN114268398A CN114268398A CN202111561422.2A CN202111561422A CN114268398A CN 114268398 A CN114268398 A CN 114268398A CN 202111561422 A CN202111561422 A CN 202111561422A CN 114268398 A CN114268398 A CN 114268398A
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Abstract
The invention discloses a simulation algorithm of a suzuki channel, which comprises the following steps: s1: generating Np paths of complex Gaussian noise with the mean value of 0 and the variance of 1, wherein the variance of each of I, Q paths is 1, and then using a Jakes Doppler filter to obtain the unit impulse response of the given Jakes Doppler filter; s2: respectively passing the Np paths of complex Gaussian noises with the mean value of 0 and the variance of 2 through corresponding Jakes Doppler filters to obtain Np complex time domain forms of distinguishable multipath fading channels with Jakes spectrums; s3: and inserting spline interpolation of RayLeigh distribution into the lognormal sequence to realize multiplication of each channel and the lognormal distribution sequence to obtain a time domain signal sequence obeying Suzuki distribution. At present, there are two models of flat fading channel, namely a Clarke channel model for describing small-scale fading and a Suzuki channel model for describing large-scale fading and small-scale fading simultaneously.
Description
Technical Field
The invention relates to a fading channel simulation algorithm of wireless communication, in particular to a suzuki (Suzuki) fading channel simulation method.
Background
Compared with a traditional Rayleigh or Rice wireless channel model, the Suzuki channel model can better represent fading characteristics, is formed by combining a Rayleigh channel and lognormal distribution and comprises characteristics of small-scale fading and medium-scale fading. Therefore, the Suzuki fading channel is widely applied in modeling test. Because the matching verification of the actual measurement model of the Suzuki fading channel is almost blank at present, a whole set of effective algorithm is required for supporting.
The classical Suzuki process is a product of the rayleigh process and the lognormal distribution process, which describe small-scale fading and large-scale fading with the rayleigh process and the lognormal distribution process, respectively. Under the Rayleigh model, the channel amplitude statistical characteristic obeys Rayleigh distribution, the phase angle statistical characteristic obeys uniform distribution, and the Doppler power spectrum is a classic Jaces power density function. However, the channel model can only embody a small-scale mobile wireless channel model, and cannot embody a mesoscale fading process more carefully, so that the aim is to provide a simulation algorithm of the suzuki channel.
Disclosure of Invention
The technical problem to be solved by the invention is that the existing simulation method of the suzuki channel is missing, and an effective simulation experiment cannot be realized.
The invention is realized by the following technical scheme:
a simulation algorithm for a suzuki channel, the algorithm comprising the steps of:
s1: generating Np paths of complex Gaussian noise with the mean value of 0 and the variance of 1, wherein the variance of each of I, Q paths is 1, and then using a Jakes Doppler filter to obtain the unit impulse response of the given Jakes Doppler filter;
s2: respectively passing the Np paths of complex Gaussian noises with the mean value of 0 and the variance of 2 through corresponding Jakes Doppler filters to obtain Np complex time domain forms of distinguishable multipath fading channels with Jakes spectrums;
s3: and inserting spline interpolation of RayLeigh distribution into the lognormal sequence to realize multiplication of each channel and the lognormal distribution sequence to obtain a time domain signal sequence obeying Suzuki distribution.
At present, there are two models of flat fading channel, namely a Clarke channel model for describing small-scale fading and a Suzuki channel model for describing large-scale fading and small-scale fading simultaneously. The main wave emitted by the transmitter passes through the obstruction of the obstacle, and undergoes multiple reflection and refraction, so as to obey the lognormal distribution. The main wave also forms multiple sub-paths due to scattering of local objects in the process of arriving at the mobile terminal, each sub-path has approximately the same amplitude and randomly and uniformly distributed phase, and the time delay of arriving at the mobile terminal is also approximately the same. The sum of the signal envelopes obeys Rayleigh distribution, the parameters of the Rayleigh distribution obey logarithmic distribution, and finally a mixed distribution, namely Suzuki fading distribution is formed, and the probability distribution of the envelopes meets requirements.
Further, in step S1, the Jakes doppler filter first performs frequency domain acquisition and inversion for Jakes doppler, performs IFFT on the extracted result and takes the real part, and finally performs normalization processing to obtain the unit impulse response of the Jakes doppler filter.
Further, the lognormal sequence in step S3 first determines how many sampling points are in a time period corresponding to the mobile correlation distance according to the sampling interval and the relative motion speed, generates a gaussian distribution sequence with a given mean and standard deviation according to the sampling points, and performs spline interpolation between two adjacent points in the obtained sequence, so that the sampling time intervals of the fast fading RayLeigh distribution are matched.
Furthermore, the two 0-mean and 1-standard deviation Gaussian sequences form I, Q paths, complex signals are obtained after combination, and corresponding time domain signals are obtained through a Jakes Doppler filter. Wherein the power spectral density formula of the Jakes Doppler filter is as follows:
wherein the content of the first and second substances,
is the maximum doppler shift.
Compared with the prior art, the invention has the following advantages and beneficial effects:
1. the invention relates to a simulation algorithm of a suzuki channel, which adopts a suzuki channel simulation method, wherein the suzuki channel is a product of a Rayleigh channel and a shadow fading channel, the Rayleigh channel is used for describing small-scale fading, and the shadow fading channel is used for describing medium-scale fading, so that a small-scale fading process and a medium-scale fading process can be embodied.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
FIG. 1 is a flow chart of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to examples and accompanying drawings, and the exemplary embodiments and descriptions thereof are only used for explaining the present invention and are not meant to limit the present invention.
Examples
As shown in fig. 1, the simulation algorithm of the suzuki channel of the present invention includes the following steps:
s1: generating Np paths of complex Gaussian noise with the mean value of 0 and the variance of 1, wherein the variance of each of I, Q paths is 1, and then using a Jakes Doppler filter to obtain the unit impulse response of the given Jakes Doppler filter;
s2: respectively passing the Np paths of complex Gaussian noises with the mean value of 0 and the variance of 2 through corresponding Jakes Doppler filters to obtain Np complex time domain forms of distinguishable multipath fading channels with Jakes spectrums;
s3: and inserting spline interpolation of RayLeigh distribution into the lognormal sequence to realize multiplication of each channel and the lognormal distribution sequence to obtain a time domain signal sequence obeying Suzuki distribution.
In the step S1, the Jakes doppler filter first performs frequency domain acquisition and inversion for Jakes doppler, performs IFFT on the extracted result and takes a real part, and finally performs normalization processing to obtain a unit impulse response of the Jakes doppler filter.
The lognormal sequence in step S3 first determines how many sampling points are in the time period corresponding to the mobile correlation distance according to the sampling interval and the relative motion speed, generates a gaussian distribution sequence with a given mean value and standard deviation according to the sampling points, and performs spline interpolation between two adjacent points in the obtained sequence, so that the sampling time intervals of the fast fading RayLeigh distribution are matched.
The two 0-mean and 1-standard deviation Gaussian sequences form I, Q two paths, complex signals are obtained after combination, and corresponding time domain signals are obtained through a Jakes Doppler filter. Wherein the power spectral density formula of the Jakes Doppler filter is as follows:
wherein the content of the first and second substances,
is the maximum doppler shift.
Generating a Gaussian sequence satisfying M-expectation-standard deviation and converting the Gaussian sequence into a lognormal distribution sequence
And interpolating it to
The sampling time intervals of the resulting fast fading Rayleigh distribution match. If random variable
Obey a gaussian distribution, i.e. a probability density function as follows:
wherein the content of the first and second substances,
it is expected that the temperature of the molten steel,
is that is
A Gaussian sequence of standard deviations, called
Obeying the Lognormal distribution.
Finally, multiplying the two parts of signals to obtain a time domain signal sequence obeying Suzuki distribution
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (4)
1. A simulation algorithm for a suzuki channel, the algorithm comprising the steps of:
s1: generating Np paths of complex Gaussian noise with the mean value of 0 and the variance of 1, wherein the variance of each of I, Q paths is 1, and then using a Jakes Doppler filter to obtain the unit impulse response of the given Jakes Doppler filter;
s2: respectively passing the Np paths of complex Gaussian noises with the mean value of 0 and the variance of 2 through corresponding Jakes Doppler filters to obtain Np complex time domain forms of distinguishable multipath fading channels with Jakes spectrums;
s3: and inserting spline interpolation of RayLeigh distribution into the lognormal sequence to realize multiplication of each channel and the lognormal distribution sequence to obtain a time domain signal sequence obeying Suzuki distribution.
2. The simulation algorithm of the suzuki channel as claimed in claim 1, wherein the Jakes doppler filter in step S1 first performs frequency domain acquisition and inversion for Jakes doppler, performs IFFT on the squared result and takes the real part, and finally performs normalization to obtain the unit impulse response of the Jakes doppler filter.
3. The simulation algorithm of a suzuki channel as claimed in claim 1, wherein the lognormal sequence in step S3 first determines how many sampling points are in a time period corresponding to a mobile correlation distance according to a sampling interval and a relative motion speed, generates a gaussian distribution sequence with a given mean and standard deviation according to the sampling points, and performs spline interpolation between two adjacent points in the obtained sequence, so that sampling time intervals of fast fading RayLeigh distribution are matched.
4. The simulation algorithm of the suzuki channel as claimed in claim 1, wherein the two 0-mean and 1-standard deviation gaussian sequences constitute I, Q channels, which are combined to obtain a complex signal, and then a corresponding time domain signal is obtained through a Jakes doppler filter, wherein the power spectral density formula of the Jakes doppler filter is as follows:
wherein the content of the first and second substances,
is the maximum doppler shift.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107465465A (en) * | 2017-09-12 | 2017-12-12 | 合肥工业大学 | A kind of Gaussian channel emulation mode and its analogue system |
| CN107517091A (en) * | 2017-08-07 | 2017-12-26 | 合肥工业大学 | A kind of multiple fading channel emulation mode of Rayleigh circular arch |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107517091A (en) * | 2017-08-07 | 2017-12-26 | 合肥工业大学 | A kind of multiple fading channel emulation mode of Rayleigh circular arch |
| CN107465465A (en) * | 2017-09-12 | 2017-12-12 | 合肥工业大学 | A kind of Gaussian channel emulation mode and its analogue system |
Non-Patent Citations (2)
| Title |
|---|
| 刘江涛: "无线通信信道的仿真与研究", no. 8, pages 3 * |
| 牛忠霞 等: "《现代通信系统》", 国防工业出版社, pages: 163 - 165 * |
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