%% Phase Shift Keying Simulation
% This demo shows how to simulate a basic Quarternary Phase Shift Keying
% (QPSK) communication link, and to generate empirical performance curves
% that can be compared to theoretical predictions.

% Copyright 1996-2004 The MathWorks, Inc.
% $Revision: 1.12.2.5 $ $Date: 2004/04/12 23:01:29 $

%% Initializing variables
% The first step is to initialize variables for number of samples per
% symbol, number of symbols to simulate, alphabet size (M) and the signal
% to noise ratio. The last line seeds the random number generators.

nSamp = 8; numSymb = 100;   
M = 4; SNR = 14; 
seed = [12345 54321];        
rand('state', seed(1)); randn('state', seed(2));

%% Generating random information symbols
% Next, use RANDSRC to generate random information symbols from 0 to M-1.
% Since the simulation is of QPSK, the symbols are 0 through 3. The first
% 10 data points are plotted.

numPlot = 10;
rand('state', seed(1));
msg_orig = randsrc(numSymb, 1, 0:M-1);
stem(0:numPlot-1, msg_orig(1:numPlot), 'bx');
xlabel('Time'); ylabel('Amplitude');

%% Phase modulating the data 
% Use PSKMOD to phase modulate the data and RECTPULSE to upsample to a
% sampling rate 8 times the carrier frequency. Use SCATTERPLOT to see the
% signal constellation.

grayencod = bitxor(0:M-1, floor((0:M-1)/2)); 
msg_gr_orig = grayencod(msg_orig+1);
msg_tx = pskmod(msg_gr_orig,M);
msg_tx = rectpulse(msg_tx,nSamp);
h1 = scatterplot(msg_tx);
set(h1,'position',[93 680 420 420]);

%% Creating the noisy signal
% Then use AWGN to add noise to the transmitted signal to create the noisy
% signal at the receiver. Use the 'measured' option to add noise that is
% 14 dB below the average signal power (SNR = 14 dB). Plot the
% constellation of the received signal.

randn('state', seed(2));
msg_rx = awgn(msg_tx, SNR, 'measured', [], 'dB');
h2 = scatterplot(msg_rx);

%% Recovering information from the transmitted signal
% Use INTDUMP to downsample to the original information rate. Then use
% PSKDEMOD to demodulate the signal, and detect the transmitted symbols.
% The detected symbols are plotted in red stems with circles and the
% transmitted symbols are plotted in blue stems with x's. The blue stems of
% the transmitted signal are shadowed by the red stems of the received
% signal. Therefore, comparing the blue x's with the red circles indicates
% that the received signal is identical to the transmitted signal.

close(h1,h2);
msg_rx_down = intdump(msg_rx,nSamp);
msg_gr_demod = pskdemod(msg_rx_down,M);
[dummy graydecod] = sort(grayencod); graydecod = graydecod - 1;
msg_demod = graydecod(msg_gr_demod+1)';
stem(0:numPlot-1, msg_orig(1:numPlot), 'bx'); hold on;
stem(0:numPlot-1, msg_demod(1:numPlot), 'ro'); hold off;
axis([ 0 numPlot -0.2 3.2]); xlabel('Time'); ylabel('Amplitude');

%% Comparing original message to demodulated message
% Finally, use BITERR and SYMERR to compare the original message to the
% demodulated message. BITERR is used to determine the bit error rate and
% SYMERR is used to determine the symbol error rate. 

[errorBit ratioBit] = biterr(msg_orig, msg_demod, log2(M));
[errorSym ratioSym] = symerr(msg_orig, msg_demod);

%% Running simulation examples
% The next step executes an example file SIMBASEBANDEX, which is a complete
% simulation example for QPSK. It demonstrates how to create simulation
% drivers in MATLAB that plot the simulation results as they are generated.

%% Running the QPSK simulation example 
% The green and magenta lines are the theoretical bit error rate (BER) and
% symbol error rate (SER) performance curves for QPSK, respectively. The
% example, SIMBASEBANDEX, plots the simulated BER and SER in red and blue
% lines, respectively. SIMBASEBANDEX uses PSKMOD and PSKDEMOD to simulate
% PSK at baseband using a complex envelope representation of the modulated
% signal.

simbasebandex(0:5);