Description
Preliminaries
In this laboratory, we cover the noise in frequency modulation (FM). For FM, the frequency of the carrier
signal changes depending on the amplitude of the message signal. In addition to these works, in this week, we
include the noise to our consideration. The term noise is used to represent unwanted waves that disturb the
transmission. While simulating our analog systems, we can generate noise by using some built-in functions
in Matlab. For this laboratory, it is useful to learn about the Matlab functions load(.), fmdemod(.), awgn(.)
and sound(.).
9 Labwork (FM in noise)
9.1 Construction
a) Load the sound file ”gong” that is given in the Matlab library by using load() function.
b) Take the signal and sampling frequency Fs from 1×1 struct as the message signal m(t) and sampling
frequency respectively fs. Hint:x=load(’gong’), mt=x.y, mt=mt’, fs=x.Fs
c) Obtain time vector t = 0:(1/fs):(numel(mt) – 1)/fs where mt is the message signal.
d) Construct the carrier signal where c(t) = cos(2πfct), with fc = 2kHz.
9.2 Modulation
a) Obtain FM signal Xfm with kf = 10000. Hint: There is no restriction on taking integral. Do not use
fmmod(.)
b) Add additive white Gaussian noise (AWGN) with signal to noise ratio (SNR) values of 0dB, 5dB,10dB
and 20dB using awgn() to your modulated Xfm.
9.3 Demodulation and Filtering
a) Demodulate your FM signals using fmdemod() function and using a low pass filter (LPF) with suitable
filter order.
b) After filtering, you will obtain the demodulated message vectors.
c) Listen to the demodulated message vectors with different SNR values by using sound() function.
d) Comment on the sound quality.
9.4 Mean Square Error (MSE) and comparison
a) Use the MSE function from previous lab to calculate the MSE values of the filtered signals with 4 different
SNR values and message signal.
b) Plot the calculated MSE values with respect to SNR.
c) Comment on the result.
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