How Do You Implement a Binary Continuous-Phase FSK Modulator in MATLAB?

[StumpyHuck29]

FSk Modulator/MATLAB Please Help!

I truly have no idea what I am doing and I am awful at MATLAB. My senior elective Digital Communications course has been plaguing me with it.

Use MATLAB to implement a binary continuous-phase FSK modulator. Make the symbols 100 samples long and the carrier have 10 samples/cycle. One approach is to first generate a data signal, data(k), in which each bit value(+1 or -1) is repeated 100 times. Next, generate the phase of the FSK signal as:

phi(k)=phi(k-1)+2*pi/10+data(k)*h*pi/100

where the second term on the right is the phase increment for each sample due to the carrier and the third term is the phase increment due to the data. The FSK signal is s(k)=cos[phi(k)]



a)Generate Sunde's FSK(h=1) for 10000 random data bits. Plot and estimate the power spectrum of the signal, i.e. plot 20*log10(abs(fft_output))




My attempt:

h=1;
data= [1 -1 1 -1 1 -1 1 1 -1 1
1 -1 1 -1 -1 1 -1 1 1 1
-1 -1 -1 1 1 1 -1 1 -1 1
-1 1 -1 1 1 1 -1 -1 1 -1
1 1 -1 1 -1 -1 1 -1 1 1
-1 1 -1 1 1 1 -1 -1 -1 -1
1 -1 1 -1 1 -1 -1 1 -1 1
1 -1 -1 -1 1 -1 1 1 1 1
1 1 1 1 -1 1 -1 1 1 -1
-1 1 1 -1 1 -1 1 -1 -1 -1];
phase=data-1+2*pi/10+data*h*pi/100;
s=cos(phase);
fs=fft(phase);
plot(fs);

 

[KataKoniK]

%plotting the power spectrum of the signal
power_spectrum=20*log10(abs(fs)); %estimating the power spectrum of the signal
plot(power_spectrum); %plotting the estimated power spectrum of the signal

b) Explain the steps you took in your attempt.


In my attempt, I first defined the value of h as 1 and then created a 100x10 matrix of random binary data bits. This represents the symbols that will be used in the FSK modulation. Then, using the given formula, I calculated the phase of the FSK signal for each sample. This was done by adding the previous phase value, the phase increment due to the carrier, and the phase increment due to the data. Next, I used the cosine function to calculate the FSK signal for each sample.

To plot the power spectrum of the signal, I used the FFT (Fast Fourier Transform) function to convert the signal from the time domain to the frequency domain. This allowed me to see the frequency components present in the signal. I then used the 20*log10(abs(fft_output)) formula to estimate the power spectrum of the signal and plotted it on a graph. This showed the power of each frequency component in the signal.

b) Overall, the steps I took were to generate the data signal, calculate the phase of the FSK signal, and then use the FFT function to plot the power spectrum of the signal. This allowed me to visualize the frequency components present in the signal and estimate their power.