bb2.py

#! /usr/bin/env python


# bb2 Project

#
# License: see LICENSE.md
#
# Copyright (C) 2021  Neal Patwari
#
# 
# Author: Neal Patwari, npatwari@wustl.edu
#
# Version History:
#
# Version 1.0:  Initial Release.  Feb 2021.  For Python 3.6.10
# Version 1.1: For class Spring 2023.
#

import sys
import numpy as np
import scipy.spatial.distance as dist
import matplotlib.pyplot as plt
import matplotlib
import scipy.signal
import scipy.io
import digicomm


matplotlib.rc('xtick', labelsize=16) 
matplotlib.rc('ytick', labelsize=16) 
plt.ion()


#################################################
# Signal Generation
# INPUT:  none
# OUTPUT: binary data
temp      = 'ESE 471';
data      = digicomm.text2bits(temp);


#################################################
# Modulation
# INPUT: data
# OUPUT: modulated values, x
symbolNumToValue = {
    0: -1, 
    1: +1
}
x = np.array([symbolNumToValue[b] for b in data])

#################################################
# Upsample
# INPUT: modulated values, x
# OUTPUT: modulated values at sampling rate, x_s
T_s = 16
x_s = digicomm.oversample( x, T_s)

#################################################
# Pulse-shape filter
# INPUT: modulated values at sampling rate, x_s
# OUTPUT: baseband transmit signal s
pulse = np.sqrt(1./T_s)*np.ones(T_s)
s     = np.convolve(x_s, pulse)

# Plot for project handout
plt.figure(1)
plt.plot(s, '-o', linewidth=2)
plt.ylim([-0.5, 0.5])
plt.xlim([0, len(s)])
plt.xlabel('Sample', fontsize=16)
plt.ylabel('Value', fontsize=16)
plt.grid('on')



# Load s if doing the receiver assignment from a saved mat file
#temp = scipy.io.loadmat('bb2.mat')
#s    = temp['s'].flatten()

#################################################
#################################################
# Bipolar, baseband PAM receiver
#################################################
#################################################

#################################################
# Matched filter
# INPUT: baseband transmitted signal s
# OUTPUT: matched-filtered signal y
pulse = np.sqrt(1./T_s)*np.ones(T_s)
y = scipy.signal.lfilter(pulse, 1, s);


# Plot for project handout
plt.figure(2)
plt.plot(y, '-o', linewidth=2)
plt.ylim([-1.5, 1.5])
plt.xlim([0, len(y)])
plt.xlabel('Sample', fontsize=16)
plt.ylabel('Value', fontsize=16)
plt.grid('on')


#################################################
# Time Synch
# Input: Matched Filter output
# OUTPUT: Synched MF output with samples at US_Rate, 2*US_Rate, ...
# *** Note: User must set this by looking at y and seeing the 
#     first index at which the first symbol sample should be read.
y_s  = y[15:]

# Plot eye-diagram
offset = 0
plt.figure(3)
digicomm.plot_eye_diagram(y_s, T_s, offset)

#################################################
# Downsample
# INPUT: Synched matched filter output
# OUTPUT: Symbol Samples (at n*T_s)
r_hat     = y_s[range( T_s-1, len(y_s), T_s)] 

#################################################
# Bit decisions
# INPUT: Symbol Samples
# OUTPUT: Bits
data_out = (r_hat>0).astype(int)

#################################################
# Translate to ascii text
# INPUT: Bits
# OUTPUT: Character vector, message_out
message_out = digicomm.binvector2str(data_out)
print(message_out)