%  This script demonstrates encoding a binary sequence to a baseband
%  line signal, and the effects of adding noise and distortion.  Plots are
%  generated to help understand the impact of noise and bandwidth limits on
%  the received waveform and potential for bit errors in the decoded
%  sequence.  The script uses the function MODULB (must be downloaded
%  from EE422G web site as well) to generate various line codes.  The
%  script initializes with critical parameters such as data rate, bit
%  sequence, line code, channel bandwidth and signal to noise level.  It
%  then plots the line coded sequence (Figure 1 of Lab Assignment), the
%  undistorted sequence with noise (Figure 2), and the noise plus distortion
%  sequence (Figure 3).  If very long sequences are used it may be better to
%  comment out the plotting code, which is located at the end of the script.
%  Beyond 12 bits it becomes difficult to observe details from the plots.
%  
%   Written by Kevin D. Donohue (donohue@engr.uky.edu) October 2007

clear
fs = 100000; %  samples/sec, sampling rate on output waveform
dr = 1000;  %  bits/sec, bit rate, should be less than fs/10 for a good simulation
snr = 30;  % Signal to noise ratio in dB for AWGN
%  Channel bandwidth model
bw = 15000; %  Hz
[b,a] = butter(4, bw/(fs/2));  % use a Butterworth LPF as channel Model

%  Line code options in cell array:
lncds = {'unipolar_nrz'; ...
         'bipolar_nrz'; ...
         '4level_nrz'; ...
         'bipolar_rz'; ...
         'unipolar_rz'; ...
         'ami'; ...
         'manchester'; ...
         'miller'; ...
         'unipolar_nyquist'; ...
         'bipolar_nyquist'};
linecode = 9;  %  Select line code
%  Binary sequence:
%seq = round(rand(1,1000));  %  Uncommment this for a random sequence
%seq = [1 0 1 0 0 0 1 1 0 1 0 1 0];  %  Uncomment this for a fixed sequence
seq = [0 0 1 0 0];
%
% Create line signal
%
[y,t] = modulb(seq,dr,fs,lncds{linecode});
%
%  Distort signal based on limited bandwidth
%
yd = filtfilt(b,a,y);   %  Band-Limited Channel 
%
%  Add noise at specified SNR
%
sigrms = sqrt(mean(y.^2));  %  Signal power in rms
% scale power in noise relative to signal
npow = sigrms*10^(-snr/20);  %  Noise power in rms
nossig = randn(size(yd));  %  Create Noise signal
yn = y+npow*nossig;  %  Add scaled noise to undistorted signal
ynd = yd+npow*nossig;  %  Add scaled noise to distorted signal

%  Plot results

%  Line signal plot
figure(1)
plot(t,y)
xlabel('Seconds')
ylabel('Volts')
title([lncds{linecode},' line signal representing binary sequence'],'Interpreter','none')
%  Extend y-axis to see signal ends and put text on top
ylow = min(y);  % Find signal low points 
yhigh = max(y);  % Find signal high points
set(gca,'Ylim', [ylow(1)-.15, yhigh(1)+.15])  %  Add a little to both ends of y-axis
%  Write binary sequence above signal in the center of time interval
%  Create a signal bit template to get bit length
template0 = modulb([0],dr,fs,lncds{linecode}); 
for k=1:length(seq)
    xpoint = length(template0)/(2*fs)+(k-1)/dr;
    text(xpoint, max(y)+.05, int2str(seq(k)))
end
%  Write lines at boundaries of each bit signal
hold on
for k =1:length(seq)
    xpoint = length(template0)/(2*fs)+ (k-1.5)/dr;
    plot([xpoint, xpoint], [ylow(1)-.15, yhigh(1)+.15], 'g:')
end
hold off
    


%  Plot of line signal with noise
figure(2)
plot(t,yn)
xlabel('Seconds')
ylabel('Volts')
title([lncds{linecode},' line signal representing binary sequence with ' num2str(snr) ...
    'dB snr'],'Interpreter','none');
%  Extend y-axis to see signal ends and put text on top
ylow = min(yn);  % Find signal low points 
yhigh = max(yn);  % Find signal high points
set(gca,'Ylim', [ylow(1)-.15, yhigh(1)+.15])  %  Add a little to both ends of y-axis
%  Write binary sequence above signal in the center of time interval
for k=1:length(seq)
    xpoint = length(template0)/(2*fs)+(k-1)/dr;
    text(xpoint, max(y)+.05,int2str(seq(k)))
end
%  Write lines at boundaries of each bit signal
hold on
for k =1:length(seq)
    xpoint = length(template0)/(2*fs)+ (k-1.5)/dr;
    plot([xpoint, xpoint], [ylow(1)-.15 yhigh(1)+.15], 'g:')
end
hold off



%  Plot of line signal with noise and channel distortion
figure(3)
plot(t,ynd)
xlabel('Seconds')
ylabel('Volts')
title([lncds{linecode},' line signal representing binary sequence with channel bandwidth of ' ...
       num2str(bw), ' Hz'],'Interpreter','none')
%  Extend y-axis to see signal ends and put text on top
ylow = min(ynd);  % Find signal low points 
yhigh = max(ynd);  % Find signal high points
set(gca,'Ylim', [ylow(1)-.15, yhigh(1)+.15])  %  Add a little to both ends of y-axis
%  Write binary sequence above signal in the center of time interval
for k=1:length(seq)
    xpoint = length(template0)/(2*fs)+(k-1)/dr;
    text(xpoint, max(y)+.05,int2str(seq(k)),'Color','r')
end
%  Write lines at boundaries of each bit signal
hold on
for k =1:length(seq)
    xpoint = length(template0)/(2*fs)+ (k-1.5)/dr;
    plot([xpoint, xpoint], [ylow(1)-.15 yhigh(1)+.15], 'g:')
end
hold off