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Summary
| Description |
English: Power Spectral Densities of the MSK, BPSK and QPSK.
Developed according to J.P. Linnartz's MATLAB script |
| Date | |
| Source | Own work |
| Author | Kirlf |
| PNG development |  This plot was created with Matplotlib. |
| Source code | Python codeimport numpy as np
import matplotlib.pyplot as plt
def normal(x):
for idx, item in enumerate(x):
if item < -100:
x[idx] = None
return x
f = np.array([i for i in range(-300, 300, 1)])/100
msk = normal(10*np.log10( (16 / (np.pi**2) )\
* (np.cos(6.2832 * f))**2 / (1 - 16 * f**2)**2 ))
bpsk = normal(10*np.log10( 2 * (np.sin(np.pi*f)/(np.pi*f))**2 ))
qpsk = normal(10*np.log10( 2 * (np.sin(2*np.pi* f)/(2*np.pi*f))**2 ))
fig = plt.figure(figsize=(7, 4), dpi=300)
plt.plot(f, bpsk, label='BPSK', color='orange')
plt.plot(f, qpsk, label='QPSK', color='blue')
plt.plot(f, msk, label='MSK', color='green')
plt.title("Normalized Power Spectral Density")
plt.xlabel('Frequency Offset / Bit Rate (Hz/bit/s)')
plt.ylabel('Spectral Power Level (dB)')
plt.legend()
plt.grid()
plt.savefig('PSD.png')
|
Licensing
I, the copyright holder of this work, hereby publish it under the following license:
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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.
File history
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| Date/Time | Thumbnail | Dimensions | User | Comment | |
|---|---|---|---|---|---|
| current | 11:31, 29 December 2018 | | 2,100 × 1,200 (246 KB) | Kirlf | User created page with UploadWizard |
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