clear;
bits = 64;
threshold = 0.5;

%Generate 64 random values. Check help on rand() function.
data = rand(1, bits);

%Quantize the random values only between two levels; 0 and 1.
for i=1:length(data)
    if data (i) > threshold
        data2(i) = 1;
    else
        data2(i) = 0;
    end
end

%Commands for plotting the data.
subplot(5, 1, 1); 
stairs(data2)
title('Original Digital Data');
ylabel('Amplitute');
axis([0 bits -0.2 1.2]);
grid off;


%%%%%%%%%%%%%%%Genrate Gaussian Noise%%%%%%%%%%%%%%%%%%%%%%
%%Different values for standard deviation for noise
sn = 0.12:0.3:1.8;
for i=1:length(sn)
    %%Generare different noise vectors.
    noise1 = randn(1, bits)*sn(i);   
    
    %%Add noise to original data;
    recv_x = data2+noise1;
    
    %%Note the figures. As the noise level increases the data becomes increasingly corrupted.
    subplot(5, 1, i+1); 
    stairs(recv_x)
    title('Received data mixed with noise');
    ylabel('Amplitute');
    axis([0 bits -2 2]);
    
   for i=1:length(recv_x)
    if recv_x(i) > threshold
        recv_data(i) = 1;
    else
        recv_data(i) = 0;
    end
   end
 
    
    
end