DANKIUM

%% Setup
N=1000;
Eavg=1;
E_noise=.01;

%% Contellation Creation
PSK_const(:,1)=sqrt(Eavg)*cos(0:pi/8:15*pi/8);
PSK_const(:,2)=sqrt(Eavg)*sin(0:pi/8:15*pi/8);

PAM_const = ((0:15)-7.5)';
PAM_const = PAM_const/sqrt(sum(PAM_const.^2)/16)*sqrt(Eavg);

QAM_const = zeros(16,2);
for i=0:3
    QAM_const((4*i+1):4*(i+1),1)=(i-1.5);
    QAM_const((i+1):4:end,2) = (i-1.5);
end
QAM_const = QAM_const/sqrt(sum(sum((QAM_const).^2))/16)*sqrt(Eavg);

%% Transmit Sequence Creation
PSK_symbols = ceil(16*rand(1,N));
PSK_transmit = PSK_const(PSK_symbols,:);

PAM_symbols = ceil(16*rand(1,N));
PAM_transmit = PAM_const(PAM_symbols);

QAM_symbols = ceil(16*rand(1,N));
QAM_transmit = QAM_const(QAM_symbols,:);

%% Channel
Z = sqrt(E_noise)*randn(N,5);

PSK_receive = PSK_transmit + Z(:,1:2);
PAM_receive = PAM_transmit + Z(:,3);
QAM_receive = QAM_transmit + Z(:,4:5);

%% Decision Rule
PAM_decision = zeros(size(PAM_symbols));
PSK_decision = zeros(size(PSK_symbols));
QAM_decision = zeros(size(QAM_symbols));

for iSample = 1:N
    [temp PAM_decision(iSample)] = min(abs(PAM_receive(iSample)-PAM_const));
    [temp PSK_decision(iSample)] = min(abs(PSK_receive(iSample,1)-PSK_const(:,1)).^2 + abs(PSK_receive(iSample,2)-PSK_const(:,2)).^2);
    [temo QAM_decision(iSample)] = min(abs(QAM_receive(iSample,1)-QAM_const(:,1)).^2 + abs(QAM_receive(iSample,2)-QAM_const(:,2)).^2);
end

%% Statistics
PAM_error_rate = sum(PAM_decision ~= PAM_symbols)/N;
PSK_error_rate = sum(PSK_decision ~= PSK_symbols)/N;
QAM_error_rate = sum(QAM_decision ~= QAM_symbols)/N;

%% Plots
figure;
subplot(2,1,1)
plot(PAM_receive(:,1),zeros(size(PAM_receive)),'b.')
title('Received PAM scatterplot')
xlabel('V_1')
ylabel('V_2')
subplot(2,2,3)
plot(PSK_receive(:,1), PSK_receive(:,2),'b.')
title('Received PSK scatterplot');
xlabel('V_1')
ylabel('V_2')
subplot(2,2,4)
plot(QAM_receive(:,1), QAM_receive(:,2),'b.')
title('Received QAM scatterplot');
xlabel('V_1')
ylabel('V_2')