A signal on a noisy channel is input to a filter

In summary, the mean-square deviation of the output signal Z(t) can be expressed in terms of the power spectral densities of the input signal X(t) and the noise signal N(t). This can be calculated using the frequency response of the linear system and integration. The steps (i) and (ii) are derived using the properties of convolution and the fact that the impulse response of the filter is zero-mean and independent of the input signal.
  • #1
JohanL
158
0
This is not homework. I am doing old exams so i have the full solution but need help understanding it.

1. Homework Statement

A WSS random signal {X(t)}t∈R with PSD S_X(ω) is transmitted on a noisy channel where it is disturbed by an additive zero-mean WSS random noise {N(t)}t∈R that is independent of the signal X and has PSD S_N (ω).

The recived signal Y (t) = X(t)+N(t) is input to a linear system (/filter) with output signal Z(t) that has frequency response

##H(ω) = S_X (ω)/(S_X (ω) + S_N (ω)).##

Express the mean-square deviation

##E((Z(t)− X(t))^2)##

in terms of

##S_X , S_N##.3. The solution

Writing h for the impulse response of the filter and ⋆ for convolution the fact that h ⋆ N is zero-mean and independent of X (as N is) readily gives that

##E((Z(t) − X(t))^2) = E(((h ⋆X)(t) + (h ⋆N)(t) − X(t))^2) =##

##(i) = E((((h−δ)⋆X)(t) + (h ⋆N)(t))^2) =##

##= E(((h−δ)⋆X)(t)^2 + (h⋆N)(t)^2) = #### (ii) = 1/2π \int^{+\infty}_{-\infty} [|H(ω)−1|^2 S_X(ω) + |H(ω)|^2 S_N(ω)] dω = ##

##. . . = 1/2π \int^{+\infty}_{-\infty} S_X(ω)S_N(ω)/(S_X (ω) +S_N(ω)) dω ##

**************************

I don't understand how you get to lines (i) and (ii) and i can't find any definitions that explains those steps.
 
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  • #2
JohanL said:
This is not homework. I am doing old exams so i have the full solution but need help understanding it.

1. Homework Statement

A WSS random signal {X(t)}t∈R with PSD S_X(ω) is transmitted on a noisy channel where it is disturbed by an additive zero-mean WSS random noise {N(t)}t∈R that is independent of the signal X and has PSD S_N (ω).

The recived signal Y (t) = X(t)+N(t) is input to a linear system (/filter) with output signal Z(t) that has frequency response

##H(ω) = S_X (ω)/(S_X (ω) + S_N (ω)).##

Express the mean-square deviation

##E((Z(t)− X(t))^2)##

in terms of

##S_X , S_N##.3. The solution

Writing h for the impulse response of the filter and ⋆ for convolution the fact that h ⋆ N is zero-mean and independent of X (as N is) readily gives that

##E((Z(t) − X(t))^2) = E(((h ⋆X)(t) + (h ⋆N)(t) − X(t))^2) =##

##(i) = E((((h−δ)⋆X)(t) + (h ⋆N)(t))^2) =##

##= E(((h−δ)⋆X)(t)^2 + (h⋆N)(t)^2) = #### (ii) = 1/2π \int^{+\infty}_{-\infty} [|H(ω)−1|^2 S_X(ω) + |H(ω)|^2 S_N(ω)] dω = ##

##. . . = 1/2π \int^{+\infty}_{-\infty} S_X(ω)S_N(ω)/(S_X (ω) +S_N(ω)) dω ##

**************************

I don't understand how you get to lines (i) and (ii) and i can't find any definitions that explains those steps.

What are WSS and PSD? I can guess the first one, but why should I need to? I cannot even guess about the second one.
 
  • #3
Ray Vickson said:
What are WSS and PSD? I can guess the first one, but why should I need to? I cannot even guess about the second one.

Sorry, WSS = Wide sense stationary and PSD = Power spectral density
 

1. What is a noisy channel?

A noisy channel refers to a communication channel where there is interference or disturbance that can affect the transmission of a signal. This interference can cause errors in the received signal, making it difficult to accurately interpret the original input.

2. What is a signal?

A signal is a physical quantity that carries information. In the context of communication, a signal can refer to an electrical, electromagnetic, or acoustic wave that is used to transmit data from one point to another. Examples of signals include radio waves, sound waves, and light waves.

3. What is a filter?

A filter is an electronic or digital device that is used to remove unwanted components from a signal. Filters are designed to selectively allow certain frequencies or components of a signal to pass through while attenuating or blocking others. In the context of a noisy channel, a filter can be used to reduce the effects of interference and improve the quality of the received signal.

4. How does a filter work?

A filter works by using a combination of electronic components, such as resistors, capacitors, and inductors, to selectively alter the amplitude, phase, or frequency of a signal. This allows the filter to attenuate or block certain frequencies or components of the signal, while passing others through to the output.

5. Why is a filter necessary for a signal on a noisy channel?

A filter is necessary for a signal on a noisy channel because it can help to improve the quality and reliability of the received signal. By removing unwanted components or interference, a filter can make it easier to accurately interpret the original input and reduce errors in the transmission. This is especially important in communication systems where a high level of accuracy is required, such as in scientific experiments or medical devices.

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