Signal Transmission Through A Linear System, Signal Distortion Over A Communication Channel, Measure of Signals, ESD and PSD of Modulated Signals
Signal Transmission Through A Linear System, Signal Distortion Over A Communication Channel, Measure of Signals, ESD and PSD of Modulated Signals
Signal Transmission Through A Linear System, Signal Distortion Over A Communication Channel, Measure of Signals, ESD and PSD of Modulated Signals
Submitted By
Name: _________________________
Section: _________________________
Submitted To
Dr. Adil Zulfiqar
Assistant Professor – EE Department
Submission Date
___ September 2021
Q1.
Q2. A certain channel has ideal amplitude, but nonideal phase response (Fig.1), given by (10)
|H ( ω )|=1
θh ( ω )=−ω t 0−ksinωT k ≪1
Show that y (t) , the channel response to an ideal pulse g(t ) band limited to B Hz is
k
y ( t ) =g ( t−t 0 ) + [ g ( t−t 0−T ) −g(t−t 0 +T )]
2
Fig.1
Q3. Signals g1 ( t )=104 rect (10 4 t) and g2 ( t ) =δ( t) are applied at the inputs of the ideal low-pass
20,000
filters whose impulse responses are h1 ( t )= sinc (20,000 t) and
t
10,000
h2 ( t ) = sinc (10,000t ) fig (2). The outputs y 1 (t ) and y 2 ( t ) of these filters are multiplied to
t
obtain the signal y ( t ) = y 1 ( t ) y 2 ( t ) .
Fig. 2
a) Sketch G 1 (w) and G 2 (w) .
b) Sketch H 1 (w) and H 2 (w) .
c) Sketch Y 1 (w) and Y 2 (w) .
CLO Taxonomy
CLO Statement Domain
No. Level
Analyze the energy, and power spectral density of the
2 Cognitive 4
transmitted signal.
Q4. Show that for a power signal, the PSD S g (w) is the Fourier transform of the autocorrelation
function R g (τ ) by using the concept of truncated power signal.
Q5. Find the autocorrelation function and power spectral density of the following function:
x ( t )=ℜ¿
Hint: e jωt =cos ωt + jsinωt convert above x(t) into 2+ A cos (ωt +θ) and then use this function for
Autocorrelation.
Q6. Find the mean Square value of (or Power) of the output voltage y (t) of the system shown in the
figure.3. if the input voltage PSD is S x ( ω )=rect ( ω/2). Calculate the power of input signal x (t ).
Fig.3