ASK & FSK

Aim

Write a simple Python program for the modulation and demodulation of ASK and FSK.

Tools required

FSK Program

import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import butter, lfilter

def butter_lowpass_filter(data, cutoff, fs, order=5):
    nyquist = 0.5 * fs
    normal_cutoff = cutoff / nyquist
    b, a = butter(order, normal_cutoff, btype='low', analog=False)
    return lfilter(b, a, data)

fs = 1000
f1 = 30
f2 = 70
bit_rate = 10
T = 1
t = np.linspace(0, T, int(fs * T), endpoint=False)

bits = np.random.randint(0, 2, bit_rate)
bit_duration = fs // bit_rate
message_signal = np.repeat(bits, bit_duration)

carrier_f1 = np.sin(2 * np.pi * f1 * t)
carrier_f2 = np.sin(2 * np.pi * f2 * t)

fsk_signal = np.zeros_like(t)
for i, bit in enumerate(bits):
    start = i * bit_duration
    end = start + bit_duration
    freq = f2 if bit else f1
    fsk_signal[start:end] = np.sin(2 * np.pi * freq * t[start:end])

ref_f1 = np.sin(2 * np.pi * f1 * t)
ref_f2 = np.sin(2 * np.pi * f2 * t)

corr_f1 = butter_lowpass_filter(fsk_signal * ref_f1, f2, fs)
corr_f2 = butter_lowpass_filter(fsk_signal * ref_f2, f2, fs)

decoded_bits = []
for i in range(bit_rate):
    start = i * bit_duration
    end = start + bit_duration
    energy_f1 = np.sum(corr_f1[start:end] ** 2)
    energy_f2 = np.sum(corr_f2[start:end] ** 2)
    decoded_bits.append(1 if energy_f2 > energy_f1 else 0)
decoded_bits = np.array(decoded_bits)
demodulated_signal = np.repeat(decoded_bits, bit_duration)

plt.figure(figsize=(12, 12))

plt.subplot(6, 1, 1)
plt.plot(t, message_signal, color='b')
plt.title('Message Signal')
plt.grid(True)

plt.subplot(6, 1, 2)
plt.plot(t, carrier_f1, color='g')
plt.title('Carrier Signal for bit = 0 (f1)')
plt.grid(True)

plt.subplot(6, 1, 3)
plt.plot(t, carrier_f2, color='r')
plt.title('Carrier Signal for bit = 1 (f2)')
plt.grid(True)

plt.subplot(6, 1, 4)
plt.plot(t, fsk_signal, color='m')
plt.title('FSK Modulated Signal')
plt.grid(True)

plt.subplot(6, 1, 5)
plt.plot(t, demodulated_signal, color='k')
plt.title('Final Demodulated Signal')
plt.grid(True)

plt.tight_layout()
plt.show()

Output Waveform

ASK PROGRAM

import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import butter, lfilter
# Butterworth low-pass filter for demodulation
def butter_lowpass_filter(data, cutoff, fs, order=5):
  nyquist = 0.5 * fs
  normal_cutoff = cutoff / nyquist
  b, a = butter(order, normal_cutoff, btype='low', analog=False)
  return lfilter(b, a, data)
# Parameters
fs = 1000 
f_carrier = 50 
bit_rate = 10 
T = 1 
t = np.linspace(0, T, int(fs * T), endpoint=False)
# Message signal (binary data)
bits = np.random.randint(0, 2, bit_rate)
bit_duration = fs // bit_rate
message_signal = np.repeat(bits, bit_duration)
# Carrier signal
carrier = np.sin(2 * np.pi * f_carrier * t)
# ASK Modulation
ask_signal = message_signal * carrier
# ASK Demodulation
demodulated = ask_signal * carrier 
filtered_signal = butter_lowpass_filter(demodulated, f_carrier, fs)
decoded_bits = (filtered_signal[::bit_duration] > 0.25).astype(int)
# Plotting
plt.figure(figsize=(12, 8))
plt.subplot(4, 1, 1)
plt.plot(t, message_signal, label='Message Signal (Binary)', color='b')
plt.title('Message Signal')
plt.grid(True)
plt.subplot(4, 1, 2)
plt.plot(t, carrier, label='Carrier Signal', color='g')
plt.title('Carrier Signal')
plt.grid(True)
plt.subplot(4, 1, 3)
plt.plot(t, ask_signal, label='ASK Modulated Signal', color='r')
plt.title('ASK Modulated Signal')
plt.grid(True)
plt.subplot(4, 1, 4)
plt.step(np.arange(len(decoded_bits)), decoded_bits, label='Decoded Bits', color='r', marker='x')
plt.title('Decoded Bits')
plt.tight_layout()
plt.show()

Output waveform

Results

Attach the output waveform

Hardware experiment output waveform.