File:Rayleigh fading.png

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Summary

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

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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You are free:
  • to share – to copy, distribute and transmit the work
  • to remix – to adapt the work
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

Items portrayed in this file

depicts

83,919 byte

504 pixel

864 pixel

image/png

7632169e7995810f74cfdcf2e88e55f25e217ec2

File history

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Date/TimeThumbnailDimensionsUserComment
current21:12, 19 October 2021Thumbnail for version as of 21:12, 19 October 2021864 × 504 (82 KB)wikimediacommons>KirlfUploaded own work with UploadWizard

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