Amplitude Modulation Examples

These examples demonstrate amplitude modulation (AM) techniques.

Compute Symbol Error Rate

In this example, you generate a random digital signal, modulate it, add noise, demodulate the noisy signal, and compute the symbol error rate. Then you plot the noisy, modulated data in a constellation diagram. The numerical results and plot may vary due to the random input data.

Create a random digital message and a constellation diagram System object™.

M = 16; % Alphabet size, 16-QAM
x = randi([0 M-1],5000,1);

cdpts = qammod(0:M-1,M);
constDiag = comm.ConstellationDiagram( ...
    ReferenceConstellation=cdpts, ...
    XLimits=[-4 4], ...
    YLimits=[-4 4]);

Apply 16-QAM modulation and transmit the signal through an AWGN channel.

y = qammod(x,M);
ynoisy = awgn(y,15,'measured');

Demodulate the noisy data, ynoisy, to recover the message and check the symbol error rate.

z = qamdemod(ynoisy,M);
[num,errrate] = symerr(x,z)

num = 
73

errrate = 
0.0146

Plot the noisy data in a constellation diagram. The signal reference constellation has 16 precisely located points, but the noise added to the transmitted signal causes the scatter plot to have a small cluster of points scattered around each reference constellation point.

constDiag(ynoisy)

Plot Noisy 16-QAM Constellation in Simulink

This example uses:

Open Model

The doc_qam_mod model uses the Rectangular QAM Modulator Baseband block to modulate random data and applies noise to the signal by using the AWGN Channel block. After passing the symbols through a noisy channel, the model produces a constellation diagram of the noisy data by using the Constellation Diagram block. When you increase the noise level, the constellation points show increased signal distortion.

A Random Integer Generator block generates integers in the range [0,15] for a modulator configured to apply 16-QAM. The modulated signal passes through an AWGN channel, and a constellation diagram displays the resulting symbols.