File:Rayleigh fading.png

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Summary

Description
English: Developed according to [1]
Date
Source Own work
Author Kirlf
PNG development
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This plot was created with Matplotlib.
Source code
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Python code

import numpy as np
from scipy import signal
import matplotlib.pyplot as plt

fs=2*np.pi*120 / 512 # sampling frequency (rad/s / samples)
ts = 1 / 120 # sampling period

""" Filter order """
N, Wn = signal.buttord(wp=0.1, 
                       ws=0.3, 
                       gpass=3, 
                       gstop=40, 
                       analog=False, 
                       fs=fs)

""" Filter """
b, a = signal.butter(N, Wn, 'low',                           
                     analog=False)

""" Frequencies """
w, h = signal.freqz(b, a, 
                    worN=512,
                    whole=True, 
                    fs=fs)
""" Rayleigh series"""

sigma = 0.12 # variance
leng = 10000 # number of samples

""" I and Q components """
ii = np.random.randn(leng, 1) * sigma
qq = np.random.randn(leng, 1) * sigma

rayleigh = ii + 1j * qq
rayleigh = [i[0] for i in rayleigh]

""" Filtering """
ryfaux = signal.filtfilt(b, a, list(rayleigh))

ry_mod = abs(ryfaux)
t_axis = np.array([i for i in range(leng)])*ts

""" Plotting """

plt.subplots(figsize=(12, 7))

ax1 = plt.subplot(212)
ax1.margins(2, 2)
ax1.plot(t_axis, 20*np.log10(ry_mod))
ax1.axis([10, 12, -50, -10])
ax1.set_xlabel('Time (s)')
ax1.set_ylabel('Relative signal level (dB)')
ax1.set_title('Rayleigh fading series (filtered)')
ax1.grid(which='both', axis='both')

ax2 = plt.subplot(221)
ax2.plot(w * 512 / (2*np.pi), 20*np.log10(abs(h)))
ax2.axis([0, 31, -71, 0])
ax2.margins(.05) 
ax2.set_title('Doppler filter responce (Butterworth lowpass digital filter)')
ax2.set_xlabel('Frequence (Hz)')
ax2.set_ylabel('Magnitude of frequency response (dB)')
ax2.grid(which='both', axis='both')

ax3 = plt.subplot(222)
ax3.margins(x=0, y=-0.25) 
ax3.plot(t_axis, 20*np.log10(abs(np.array(rayleigh))))
ax3.axis([10, 12, -50, -10])
ax3.set_xlabel('Time (s)')
ax3.set_ylabel('Relative signal level (dB)')
ax3.set_title('Rayleigh fading series')
ax3.grid(which='both', axis='both')


plt.savefig("rayleigh_fading.png")

Licensing

I, the copyright holder of this work, hereby publish it under the following license:
w:en:Creative Commons
attribution share alike
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Under the following conditions:
  • attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  • share alike – If you remix, transform, or build upon the material, you must distribute your contributions under the same or compatible license as the original.
  1. Fontæn, F.P. and Espiæeira, P.M., 2008. Modelling the wireless propagation channel: a simulation approach with Matlab (Vol. 5). John Wiley & Sons. - p. 123 - 129

Captions

Butterworth filter response, Rayleigh time series and filtered Rayleigh time series

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Date/TimeThumbnailDimensionsUserComment
current20:12, 19 October 2021Thumbnail for version as of 20:12, 19 October 2021864 × 504 (82 KB)KirlfUploaded own work with UploadWizard
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