Signal filtering in digital transmission

In summary, the conversation discusses optimizing the detection of a signal sent with a rectangular function. This signal is processed through a filter with an impulse response of a sine function and a rectangular function translated by T/2. The output signal is y(t). The first question asks to calculate y(t) when only a0 is given, and to graphically illustrate the result. The second question asks for the general expression of y(t) and for the optimal moments to detect the values being transmitted. The third question asks to express h(t) as a convolution and determine h0(t), H0(f), and the modulus and phase of the transfer function H(f). Finally, the fourth question discusses obtaining the values from an audio signal and the use of
  • #1
LorDjidane
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Homework Statement



Let's suppose a set of numerical values {an} sent with a rectangular function, period T and with amplitude an.
The signal can be expressed as follows:
[tex]x(t)= \sum a_n \Pi_T (t-nT)[/tex]
To optimize detection at reception, the signal x(t) is processed through a filter whose impulse response is:
[tex]h(t)= sin(\frac{\pi t}{T} \Pi_T (t-\frac{T}{2})[/tex]
We write y(t) the output signal

1/ If we only have a0=A, calculate y(t) and illustrate the computed elements graphically.

2/ Express y(t) in the general case. Plot x(t) and y(t) if the values to be transmitted are ...,0,0,0,3,5,-2,1,-3,0,0,0,... What are the optimal moments to detect {an} from y(t) ?

3/ Express h(t) as a convolution:
[tex]h(t)=h_0(t)*\delta(t-\frac{T}{2})[/tex]
Determine h0(t), calculate H0(f) and give a graphical representation. What are the modulus and phase of the transfer function H(f) ?

4/ Let’s suppose the {an} are obtained after an audio signal sampling at Fe=1/T, we have an = s(nT). Give the spectrum of x(t), X(f) with a graphical representation. Express the mean value of x(t) with respect to the one of s(t), Ps. Is the filtering of x(t) by h(t) a good way to get back s(t) from x(t)? Why?

Homework Equations



[tex]x(t)= \sum a_n \Pi_T (t-nT)[/tex]

[tex]h(t)= sin(\frac{\pi t}{T} \Pi_T (t-\frac{T}{2})[/tex]

[tex]y(t)=x(t)*h(t)[/tex]

The Attempt at a Solution



Well, this is not exactly for me but for one of my students who’s having a hard time. Except he’s my student in electronics laboratories not in signal processing and since he begged me to help him, here i am getting back in signal processing. :(

My ideas:

h(t) is the multiplication of a sine with a rectangular function translated by T/2 so I can have their common area, plot it and do my convolution graphically. But I can’t carefully write the mathematical operation.
By writing the convolution :
[tex]y(t)=\int sin(\frac{\pi \tau}{T}) \Pi_T (\tau-\frac{T}{2}) A \Pi_T (t - \tau) d\tau[/tex]
But this doesn’t seem easy to compute. I thought of coming through it with a Fourier transform to get two sinc with the rectangular functions and a dirac with the sine. But I’m not sure about the carefullness of my operation.

Actually once I understand this question and the math behind it, I may be able to go on by myself. The second question is a generalization of the first and the optimal detection instants are trivial.

For the third question the dirac makes me think of a T/2 delay so h(0) would be for me the product of a sine and something doing the rectangular function but I’m not sure. Again, once started I should be able to go on by myself.

I hope this thread doesn’t seem too improper with respect to the policy here, but I’m starting to see my student’s face decomposed.
 
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  • #2
I’d be very grateful for an explanation of the first question that would help me going through this. Thank you for your time.
 

1. What is signal filtering in digital transmission?

Signal filtering in digital transmission is the process of removing unwanted noise or interference from a digital signal to improve its quality and reliability. This is typically done using digital signal processing techniques.

2. Why is signal filtering important in digital transmission?

Signal filtering is important in digital transmission because it helps to remove any unwanted noise or interference from the signal, which can distort the original data and lead to errors in transmission. This can greatly impact the overall quality and reliability of the transmitted signal.

3. What are the different types of signal filtering in digital transmission?

There are several types of signal filtering in digital transmission, including low-pass, high-pass, band-pass, and band-stop filters. Low-pass filters allow only low-frequency signals to pass through, while high-pass filters allow only high-frequency signals. Band-pass filters allow a specific range of frequencies to pass through, and band-stop filters block a specific range of frequencies.

4. How does signal filtering affect the data transmission rate?

Signal filtering can affect the data transmission rate by reducing the amount of data that is transmitted. This is because the filtering process removes some of the data as it removes the noise or interference. However, this trade-off is necessary to ensure the accuracy and reliability of the transmitted data.

5. Can signal filtering be done in real-time?

Yes, signal filtering can be done in real-time. With advancements in digital signal processing technology, it is now possible to filter signals in real-time, without any noticeable delay. This is important in applications where the data needs to be processed and transmitted quickly, such as in telecommunications or data communication systems.

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