DSB-SC Modulation and Demodulation using NumPy and Matplotlib

Aim:

To implement and analyze Double Sideband Suppressed Carrier (DSB-SC) modulation using Python's NumPy and Matplotlib libraries.

Apparatus Required:

Software: Python with NumPy and Matplotlib libraries Hardware: Personal Computer

Theory:

Double Sideband Suppressed Carrier (DSB-SC) modulation is a type of amplitude modulation where the carrier is completely suppressed, and only the upper and lower sidebands are transmitted. The modulated signal is generated by multiplying the message signal with the carrier signal. Since the carrier is absent, DSB-SC is more power-efficient than conventional AM.

Algorithm:

Initialize Parameters: Set message frequency, carrier frequency, amplitudes, and sampling frequency.

Generate Time Axis: Create a time vector for the duration of the signal.

Generate Message Signal: Create a cosine wave representing the message signal.

Generate Carrier Signal: Create a cosine wave representing the carrier signal.

Modulate Signal (DSB-SC): Multiply the message signal with the carrier signal.

Plot the Signals: Display message signal, carrier signal, and DSB-SC modulated signal using Matplotlib.

Program :

import numpy as np
import matplotlib.pyplot as plt
Am = 6.2
fm = 494
Ac = 12.4
fc = 4940
fs = 49400
t = np.arange(0, 3/fm, 1/fs)
m1 = Am * np.cos(2 * np.pi * fm * t)
m2 = Am * np.cos(1.57 - 2 * np.pi * fm * t)
c1 = Ac * np.cos(2 * np.pi * fc * t)
c2 = Ac * np.cos(1.57 - 2 * np.pi * fc * t)
s1 = c1 * m1
s2 = c2 * m2
Slsb = s1 + s2
Susb = s1 - s2
plt.figure(figsize=(10, 8))
plt.subplot(4, 1, 1)
plt.plot(t, m1)
plt.subplot(4, 1, 2)
plt.plot(t, c1)
plt.subplot(4, 1, 3)
plt.plot(t, Slsb)
plt.subplot(4, 1, 4)
plt.plot(t, Susb)
plt.tight_layout()
plt.show()

Tabulation :

Output graph:

Result:

The Double Sideband Suppressed Carrier (DSB-SC) modulation was successfully implemented using Python (NumPy and Matplotlib).