PPM Modulator

Hi, Please how can I build a PPM modulator in simulink. The block is not available in my matlab. i am using 2008b

[Fangjun Jiang]

What is PPM?

[Walter Roberson]

Pulse Position Modulation

[ska109]

I've made it working somehow...

[Yashwanth]

ppm full code

clc;

clear all;

close all;

% Binary PPM

fs = 100;

dt = 1/fs;

t1 = 0:dt:1-dt;

t2 = 1:dt:2-dt;

t = [t1 t2];

% PPM signals

s1 = [ones(1,length(t1)), zeros(1,length(t2))];

s2 = [zeros(1,length(t1)), ones(1,length(t2))];

% Plot transmitted signals

figure;

subplot(2,1,1);

plot(t,s1);

title('PPM Signal 1');

xlabel('Time (s)');

ylabel('Amplitude');

grid on;

subplot(2,1,2);

plot(t,s2);

title('PPM Signal 0');

xlabel('Time (s)');

ylabel('Amplitude');

grid on;

% Energy and first basis function

e1 = sum(s1.^2)*dt;

psi1 = s1/sqrt(e1);

% Second basis function using orthogonalization

s21 = sum(s2.*psi1)*dt;

d2 = s2-s21*psi1;

ed2 = sum(d2.^2)*dt;

psi2 = d2/sqrt(ed2);

% Plot basis functions

figure;

subplot(2,1,1);

plot(t,psi1);

title('Basis Function 1');

xlabel('Time (s)');

ylabel('Amplitude');

grid on;

subplot(2,1,2);

plot(t,psi2);

title('Basis Function 2');

xlabel('Time (s)');

ylabel('Amplitude');

grid on;

% Signal-space coordinates

s_11 = sum(s1.*psi1)*dt;

s_21 = sum(s2.*psi1)*dt;

s_12 = sum(s1.*psi2)*dt;

s_22 = sum(s2.*psi2)*dt;

figure;

stem([s_11 s_21],[s_12 s_22],'filled');

title('PPM Signal Space Representation');

xlabel('Coordinate 1');

ylabel('Coordinate 2');

grid on;

% AWGN with variances 0, 0.1, 1 and 2

n1 = sqrt(0)*randn(size(s1));

n2 = sqrt(0.1)*randn(size(s1));

n3 = sqrt(1)*randn(size(s1));

n4 = sqrt(2)*randn(size(s1));

% Received signals

r1 = s1+n1;

r2 = s1+n2;

r3 = s1+n3;

r4 = s1+n4;

r5 = s2+n1;

r6 = s2+n2;

r7 = s2+n3;

r8 = s2+n4;

% Plot received signals

figure;

subplot(4,2,1);

plot(t,r1);

title('Signal 1: Variance 0');

grid on;

subplot(4,2,2);

plot(t,r5);

title('Signal 0: Variance 0');

grid on;

subplot(4,2,3);

plot(t,r2);

title('Signal 1: Variance 0.1');

grid on;

subplot(4,2,4);

plot(t,r6);

title('Signal 0: Variance 0.1');

grid on;

subplot(4,2,5);

plot(t,r3);

title('Signal 1: Variance 1');

grid on;

subplot(4,2,6);

plot(t,r7);

title('Signal 0: Variance 1');

grid on;

subplot(4,2,7);

plot(t,r4);

title('Signal 1: Variance 2');

grid on;

subplot(4,2,8);

plot(t,r8);

title('Signal 0: Variance 2');

grid on;

% Correlation receiver

R = [r1; r2; r3; r4; r5; r6; r7; r8];

X = zeros(8,2);

for i = 1:8

X(i,1) = sum(R(i,:).*psi1)*dt;

X(i,2) = sum(R(i,:).*psi2)*dt;

end

% Plot signal-space coordinates for each variance

figure;

subplot(2,2,1);

stem(X([1 5],1),X([1 5],2),'filled');

title('Signal Space: Variance 0');

grid on;

subplot(2,2,2);

stem(X([2 6],1),X([2 6],2),'filled');

title('Signal Space: Variance 0.1');

grid on;

subplot(2,2,3);

stem(X([3 7],1),X([3 7],2),'filled');

title('Signal Space: Variance 1');

grid on;

subplot(2,2,4);

stem(X([4 8],1),X([4 8],2),'filled');

title('Signal Space: Variance 2');

grid on;

% Matched-filter impulse responses

h1 = fliplr(psi1);

h2 = fliplr(psi2);

% Matched-filter outputs for both basis functions

Y1 = zeros(8, length(t)+length(h1)-1);

Y2 = zeros(8, length(t)+length(h2)-1);

for i = 1:8

Y1(i,:) = conv(R(i,:),h1)*dt;

Y2(i,:) = conv(R(i,:),h2)*dt;

end

ty = 0:dt:2*(length(t)-1)*dt;

% Plot the matched-filter outputs

figure;

subplot(2,2,1);

plot(ty,Y1(1,:));

hold on;

plot(ty,Y1(5,:));

title('Matched Filter: Variance 0');

xlabel('Time (s)');

ylabel('Output');

legend('Signal 1','Signal 0');

grid on;

subplot(2,2,2);

plot(ty,Y1(2,:));

hold on;

plot(ty,Y1(6,:));

title('Matched Filter: Variance 0.1');

xlabel('Time (s)');

ylabel('Output');

legend('Signal 1','Signal 0');

grid on;

subplot(2,2,3);

plot(ty,Y1(3,:));

hold on;

plot(ty,Y1(7,:));

title('Matched Filter: Variance 1');

xlabel('Time (s)');

ylabel('Output');

legend('Signal 1','Signal 0');

grid on;

subplot(2,2,4);

plot(ty,Y1(4,:));

hold on;

plot(ty,Y1(8,:));

title('Matched Filter: Variance 2');

xlabel('Time (s)');

ylabel('Output');

legend('Signal 1','Signal 0');

grid on;

% Display correlation coordinates

disp('Rows: r1 through r8');

disp('Columns: basis function 1 and basis function 2');

disp(X);

[Yashwanth]

PAM

clc;

clear all;

close all;

% BINARY PAM MODULATION AND DEMODULATION

fs = 100;

dt = 1/fs;

t = 0:dt:1;

% Binary PAM signals

s1 = ones(1,length(t));

s2 = -1*ones(1,length(t));

% Plotting signals

figure;

subplot(2,1,1);

plot(t,s1);

title('Signal 1');

xlabel('Time (s)');

ylabel('Amplitude');

grid on;

subplot(2,1,2);

plot(t,s2);

title('Signal 0');

xlabel('Time (s)');

ylabel('Amplitude');

grid on;

% Energy and basis function

e1 = sum(s1.*s1)*dt;

psi1 = s1/sqrt(e1);

figure;

subplot(2,1,1);

plot(t,psi1);

title('Basis Function 1');

xlabel('Time (s)');

ylabel('Amplitude');

grid on;

% Signal space representation

s_11 = sum(s1.*psi1)*dt;

s_21 = sum(s2.*psi1)*dt;

subplot(2,1,2);

stem([s_11 s_21],[0 0],'filled');

title('Signal Space Representation');

xlabel('Signal Coordinate');

ylabel('Amplitude');

grid on;

% AWGN with different variances

n1 = sqrt(0)*randn(size(s1));

n2 = sqrt(0.1)*randn(size(s1));

n3 = sqrt(1)*randn(size(s1));

n4 = sqrt(2)*randn(size(s1));

% Received signals

r1 = s1+n1;

r2 = s1+n2;

r3 = s1+n3;

r4 = s1+n4;

r5 = s2+n1;

r6 = s2+n2;

r7 = s2+n3;

r8 = s2+n4;

% Plot received signals

figure;

subplot(4,2,1);

plot(t,r1);

title('Signal 1: Noise Variance 0');

grid on;

subplot(4,2,2);

plot(t,r5);

title('Signal 0: Noise Variance 0');

grid on;

subplot(4,2,3);

plot(t,r2);

title('Signal 1: Noise Variance 0.1');

grid on;

subplot(4,2,4);

plot(t,r6);

title('Signal 0: Noise Variance 0.1');

grid on;

subplot(4,2,5);

plot(t,r3);

title('Signal 1: Noise Variance 1');

grid on;

subplot(4,2,6);

plot(t,r7);

title('Signal 0: Noise Variance 1');

grid on;

subplot(4,2,7);

plot(t,r4);

title('Signal 1: Noise Variance 2');

grid on;

subplot(4,2,8);

plot(t,r8);

title('Signal 0: Noise Variance 2');

grid on;

% CORRELATION RECEIVER

x1 = sum(r1.*psi1)*dt;

x2 = sum(r2.*psi1)*dt;

x3 = sum(r3.*psi1)*dt;

x4 = sum(r4.*psi1)*dt;

x5 = sum(r5.*psi1)*dt;

x6 = sum(r6.*psi1)*dt;

x7 = sum(r7.*psi1)*dt;

x8 = sum(r8.*psi1)*dt;

% Correlator output plots

figure;

subplot(2,2,1);

stem([x1 x5],[0 0],'filled');

title('Correlation: Variance 0');

grid on;

subplot(2,2,2);

stem([x2 x6],[0 0],'filled');

title('Correlation: Variance 0.1');

grid on;

subplot(2,2,3);

stem([x3 x7],[0 0],'filled');

title('Correlation: Variance 1');

grid on;

subplot(2,2,4);

stem([x4 x8],[0 0],'filled');

title('Correlation: Variance 2');

grid on;

% MATCHED FILTER

h = fliplr(psi1);

figure;

plot(t,h);

title('Matched Filter Impulse Response');

xlabel('Time (s)');

ylabel('Amplitude');

grid on;

% Convolution outputs

y1 = conv(r1,h)*dt;

y2 = conv(r2,h)*dt;

y3 = conv(r3,h)*dt;

y4 = conv(r4,h)*dt;

y5 = conv(r5,h)*dt;

y6 = conv(r6,h)*dt;

y7 = conv(r7,h)*dt;

y8 = conv(r8,h)*dt;

% Convolution time axis

ty = 0:dt:2;

% Plot matched filter outputs

figure;

subplot(2,2,1);

plot(ty,y1);

hold on;

plot(ty,y5);

title('Matched Filter: Variance 0');

legend('Signal 1','Signal 0');

xlabel('Time (s)');

ylabel('Output');

grid on;

subplot(2,2,2);

plot(ty,y2);

hold on;

plot(ty,y6);

title('Matched Filter: Variance 0.1');

legend('Signal 1','Signal 0');

xlabel('Time (s)');

ylabel('Output');

grid on;

subplot(2,2,3);

plot(ty,y3);

hold on;

plot(ty,y7);

title('Matched Filter: Variance 1');

legend('Signal 1','Signal 0');

xlabel('Time (s)');

ylabel('Output');

grid on;

subplot(2,2,4);

plot(ty,y4);

hold on;

plot(ty,y8);

title('Matched Filter: Variance 2');

legend('Signal 1','Signal 0');

xlabel('Time (s)');

ylabel('Output');

grid on;

% Demodulation decision using correlator outputs

corr_out = [x1 x2 x3 x4; x5 x6 x7 x8];

disp('Correlation outputs:');

disp(corr_out);

disp('Decision: positive = Signal 1, negative = Signal 0');

disp(sign(corr_out));

Answer 1

[Walter Roberson]

http://www.mathworks.com/help/toolbox/signal/ref/modulate.html

Note that is part of the Signal Processing Toolbox.

The Technical Support note that is relevant, here says that

PPM and PWM are described in “Digital and Analog Communication Systems, 5th Ed.” by Leon Couch. Pages 209-213 describe these modulations, and show circuits that are used for the modulation.

Answer 2

[dave]

Thank you. I will look through it.

Answer 3

[sivasena reddy]

clc;
close all;
clear all;
t=0:0.001:1;
s=sawtooth(2*pi*10*t+pi);
m=0.75*sin(2*pi*1*t);
n=length(s);
for i=1:n
 if (m(i)>=s(i))
 pwm(i)=1;
 elseif (m(i)<=s(i))
 pwm(i)=0;
 end
end
plot(t,pwm,'g',t,m,'r',t,s,'--b');

ylabel('Amplitude');
axis([0  1 -1.5 1.5]);
xlabel('Time index');
title('PWM Wave');
grid on;

[Walter Roberson]

The user had requested Simulink implementation, though.

Also, you appear to be doing PWM (Pulse Width Modification) rather than PPM (Pulse Position Modification)

Answer 4

[Atul Kumar]

clc;
close all;
clear all;
t=0:0.001:1;
s=sawtooth(2*pi*10*t+pi);
m=0.75*sin(2*pi*1*t);
n=length(s);
for i=1:n
 if (m(i)>=s(i))
 pwm(i)=1;
 elseif (m(i)<=s(i))
 pwm(i)=0;
 end
end
plot(t,pwm,'g',t,m,'r',t,s,'--b');
ylabel('Amplitude');
axis([0  1 -1.5 1.5]);
xlabel('Time index');
title('PWM Wave');
grid on;

[Walter Roberson]

How does this differ from https://www.mathworks.com/matlabcentral/answers/24247-ppm-modulator#answer_374142 other than the spacing?