Module DigiCommPy.scripts.chapter_2.msk

"""
Performance MSK modulation/demodulation

@author: Mathuranathan Viswanathan
Created on Jul 24, 2019
"""
#Execute in Python3: exec(open("chapter_2/msk.py").read())
import numpy as np #for numerical computing
import matplotlib.pyplot as plt #for plotting functions
from passband_modulations import msk_mod,msk_demod
from channels import awgn 
from scipy.special import erfc

N = 100000 # Number of symbols to transmit
EbN0dB = np.arange(start=-4,stop = 11,step = 2) # Eb/N0 range in dB for simulation
fc = 800 # carrier frequency in Hertz
OF = 32 # oversampling factor, sampling frequency will be fs=OF*fc

BER = np.zeros(len(EbN0dB)) # For BER values for each Eb/N0

a = np.random.randint(2, size=N) # uniform random symbols from 0's and 1's
result = msk_mod(a,fc,OF,enable_plot=True) # MSK modulation
s = result['s(t)']

for i,EbN0 in enumerate(EbN0dB):
    # Compute and add AWGN noise
    r = awgn(s,EbN0,OF) # refer Chapter section 4.1
    
    a_hat = msk_demod(r,N,fc,OF) #receiver
    
    BER[i] = np.sum(a!=a_hat)/N # Bit Error Rate Computation

theoreticalBER = 0.5*erfc(np.sqrt(10**(EbN0dB/10))) # Theoretical bit error rate

#-------------Plots---------------------------
fig, ax = plt.subplots(nrows=1,ncols = 1)
ax.semilogy(EbN0dB,BER,'k*',label='Simulated') # simulated BER
ax.semilogy(EbN0dB,theoreticalBER,'r-',label='Theoretical')
ax.set_xlabel(r'$E_b/N_0$ (dB)')
ax.set_ylabel(r'Probability of Bit Error - $P_b$')
ax.set_title(['Probability of Bit Error for MSK modulation'])
ax.legend();fig.show();