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Difference between revisions of "Aufgaben:Exercise 4.2Z: About the Sampling Theorem"

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[[File:|right|]]
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[[File:P_ID1610__Mod_Z_4_2.png|right|frame|Harmonic oscillations of different phase]]
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The&nbsp; [[Signal_Representation/Discrete-Time_Signal_Representation#Sampling_theorem|sampling theorem]]&nbsp; states that the sampling frequency&nbsp; fA=1/TA&nbsp; must be at least twice as large as the largest frequency&nbsp; fN, max&nbsp; contained in the source signal&nbsp; q(t):
 +
:fA2fN,maxTA12fN,max.
 +
If this condition is met,&nbsp; then at the receiver the message signal can be passed through a rectangular&nbsp; (ideal)&nbsp; low-pass filter with frequency response
 +
:H(f)={11/20f¨urf¨urf¨ur|f|<fG,|f|=fG,|f|>fG
 +
can be completely reconstructed, that is, it is then&nbsp; v(t)=q(t).
 +
*The cutoff frequency&nbsp; fG&nbsp; is to be chosen equal to half the sampling frequency.
 +
*The equal sign is generally valid only if the spectrum&nbsp; Q(f)&nbsp; does not contain a discrete spectral line at frequency&nbsp; fN, max.
  
  
===Fragebogen===
+
In this exercise,&nbsp; three different source signals are considered,&nbsp; each of which can be expressed as a harmonic oscillation
 +
:$$q(t) = A \cdot \cos (2 \pi \cdot f_{\rm N} \cdot t - \varphi)$$
 +
with amplitude&nbsp; $A = 1\ \rm V&nbsp; and frequency&nbsp;f_{\rm N}= 5 \ \rm kHz.&nbsp; For the spectral function&nbsp;Q(f)$&nbsp; of all represented time signals generally holds:
 +
:Q(f)=A2δ(ffN)ejφ+A2δ(f+fN)e+jφ.
 +
The oscillations sketched in the graph differ only by the phase&nbsp; φ:
 +
* φ_1 = 0 &nbsp; ⇒ &nbsp; cosine signal&nbsp; q_1(t),
 +
* φ_2 = π/2 \ (= 90^\circ) &nbsp; ⇒ &nbsp; sinusoidal signal&nbsp; q_2(t),
 +
* φ_3 = π/4 \ (= 45^\circ) &nbsp; ⇒ &nbsp; signal&nbsp; q_3(t).
 +
 
 +
 
 +
 
 +
 
 +
 
 +
 
 +
Hints:
 +
*The exercise belongs to the chapter&nbsp; [[Modulation_Methods/Pulse_Code_Modulation|"Pulse Code Modulation"]].
 +
*Reference is made in particular to the page&nbsp; [[Modulation_Methods/Pulse_Code_Modulation#Sampling_and_signal_reconstruction|"Sampling and Signal Reconstruction"]].
 +
*The sampled source signal is denoted by&nbsp; q_{\rm A}(t)&nbsp; and its spectral function by&nbsp; Q_{\rm A}(f).&nbsp;
 +
*Sampling is always performed at&nbsp; ν \cdot T_{\rm A}.
 +
 +
 
 +
===Questions===
  
 
<quiz display=simple>
 
<quiz display=simple>
{Multiple-Choice Frage
+
{Which statements are valid with &nbsp;f_{\rm A} = 11\ \rm kHz?
 
|type="[]"}
 
|type="[]"}
- Falsch
+
+ The sampling theorem is always satisfied.
+ Richtig
+
+ All signals can be reconstructed by a low-pass filter.
 +
+ It is always true: &nbsp;Q_{\rm A}(f = 5 \ {\rm kHz}) = Q(f = 5 \ \rm kHz).
  
  
{Input-Box Frage
+
{What sampling distance results with &nbsp;f_{\rm A} = 10\ \rm kHz?
 
|type="{}"}
 
|type="{}"}
$\alpha$ = { 0.3 }
+
$T_{\rm A} \ = \ $ { 0.1 3% } \ \rm ms
 +
 
 +
{Which statements are valid for the signal &nbsp;q_1(t)&nbsp; and &nbsp;f_{\rm A} = 10\ \rm kHz?
 +
|type="[]"}
 +
- It holds &nbsp;Q_{\rm A}(f = 5 \ {\rm kHz)} = Q_1(f = 5 \ \rm kHz).
 +
+ A complete signal reconstruction is possible &nbsp; ⇒ &nbsp; v_1(t) = q_1(t).
 +
- The reconstructed signal is &nbsp;v_1(t) \equiv 0.
  
 +
{What statements hold for the signal &nbsp;q_2(t)&nbsp; and &nbsp;f_{\rm A} = 10\ \rm kHz?
 +
|type="[]"}
 +
- It holds &nbsp;Q_{\rm A}(f = 5 \ {\rm kHz)} = Q_2(f = 5 \ \rm kHz).
 +
- A complete signal reconstruction is possible &nbsp; ⇒ &nbsp; v_2(t) = q_2(t).
 +
+ The reconstructed signal is &nbsp;v_2(t) \equiv 0.
 +
 +
{What statements hold for the signal &nbsp;q_3(t) and f_{\rm A} = 10\ \rm kHz?
 +
|type="[]"}
 +
- It holds &nbsp;Q_{\rm A}(f = 5 \ {\rm kHz)} = Q_3(f = 5 \ \rm kHz).
 +
- A complete signal reconstruction is possible &nbsp; ⇒ &nbsp; v_3(t) = q_3(t).
 +
- The reconstructed signal is &nbsp;v_3(t) \equiv 0.
  
  
 
</quiz>
 
</quiz>
  
===Musterlösung===
+
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''1.'''
+
'''(1)'''&nbsp; <u>All statements</u>&nbsp; are true:
'''2.'''
+
[[File:P_ID1611__Mod_Z_4_2a.png|P_ID1611__Mod_Z_4_2a.png|right|frame|Spectral function of the sampled signal]]
'''3.'''
+
*The sampling theorem is satisfied by&nbsp; f_{\rm A} = 11 \ \rm kHz > 2 \cdot 5 \ \rm kHz&nbsp; so that a complete signal reconstruction is always possible.
'''4.'''
+
*The spectrum&nbsp; Q_{\rm A}(f)&nbsp; results from&nbsp; Q(f)&nbsp; by periodic continuation at the respective frequency spacing&nbsp; f_{\rm A},&nbsp; which is generally illustrated in the graph.
'''5.'''
+
*By a rectangular low-pass with&nbsp; f_{\rm G} = f_{\rm A}/2 = 5.5 \ \rm kHz&nbsp; the original spectrum&nbsp; Q(f) is obtained.
'''6.'''
+
 
'''7.'''
+
 
 +
The shift by
 +
* f_{\rm A} = 11 \ \rm kHz&nbsp; yields the lines at&nbsp; +6 \ \rm kHz&nbsp; and&nbsp; +16 \ \rm kHz,
 +
* -f_{\rm A} = -11 \ \rm kHz&nbsp; yields the lines at&nbsp; -6 \ \rm kHz&nbsp; and&nbsp; -16 \ \rm kHz,
 +
* 2 - f_{\rm A} = 22 \ \rm kHz&nbsp; yields the lines at&nbsp; +17 \ \rm kHz&nbsp; and&nbsp; +27 \ \rm kHz,
 +
* -2 - f_{\rm A}= -22 \ \rm kHz&nbsp; yields the lines at&nbsp; -17 \ \rm kHz, -27 \ \rm kHz.
 +
 
 +
 
 +
 
 +
'''(2)'''&nbsp; The sampling distance is equal to the reciprocal of the sampling frequency:
 +
: T_{\rm A} = {1}/{f_{\rm A} }\hspace{0.15cm}\underline { = 0.1\,{\rm ms}} \hspace{0.05cm}.
 +
 
 +
 
 +
 
 +
'''(3)'''&nbsp; The correct solution is&nbsp; <u>suggestion 2</u>:
 +
[[File:P_ID1612__Mod_Z_4_2c.png|P_ID1612__Mod_Z_4_2c.png|right|frame|Spectral function of the sampled cosine signal]]
 +
 
 +
*For the cosinusoidal signal,&nbsp; according to this graph with&nbsp; f_{\rm A} = 10 \rm \ kHz:&nbsp;  All spectral lines of&nbsp; Q_{\rm A}(f):&nbsp; are real.
 +
*The periodization of&nbsp; Q(f)&nbsp; with&nbsp; f_{\rm A} = 10 \rm \ kHz&nbsp; leads to a Dirac comb with spectral lines at&nbsp; ±f_{\rm N},&nbsp; ±f_{\rm N}± f_{\rm A},&nbsp; ±f_{\rm N}± 2f_{\rm A}, . ..
 +
*Through the superpositions,&nbsp; all Dirac functions have weight&nbsp; A,&nbsp; while the spectral lines of&nbsp; Q(f)&nbsp; are weighted only by&nbsp; A/2&nbsp; each.
 +
*Because&nbsp; H(f = f_{\rm N}) = H(f = f_{\rm G}) = 0.5&nbsp; the spectrum&nbsp; V_1(f)&nbsp; after the low-pass is identical to&nbsp; Q_1(f) &nbsp; &rArr; &nbsp; v_1(t) = q_1(t).
 +
*In the time domain, the signal reconstruction can be thought of as follows: &nbsp; The samples of&nbsp; q_1(t)&nbsp; lie exactly at the signal maxima and minima. &nbsp; 
 +
*The lowpass filter forms the cosine signal with correct amplitude, frequency and phase.
 +
<br clear=all>
 +
[[File:P_ID1613__Mod_Z_4_2d.png|P_ID1613__Mod_Z_4_2d.png|right|frame|Sampled sine signal]]
 +
'''(4)'''&nbsp; Correct is&nbsp; <u>suggested solution 2</u>:
 +
*All sampled values of&nbsp; q_2(t)&nbsp; now lie exactly at the zero crossings of the sinusoidal signal,&nbsp; which means that here&nbsp; q_{\rm A}(t) \equiv 0&nbsp; holds.&nbsp; However,&nbsp; this naturally also gives&nbsp; v_2(t) \equiv 0.
 +
*In the spectral domain,&nbsp; the result can be derived using the graph for subtask&nbsp; '''(1)'''.&nbsp; <br>⇒ &nbsp;Q(f)&nbsp; is purely imaginary and the imaginary parts at&nbsp; ±f_{\rm N}&nbsp; have different signs. &nbsp;
 +
*Thus,&nbsp; one positive and one negative part cancel each other in periodization &nbsp; <br>⇒ &nbsp; Q_{\rm A}(f) \equiv 0 &nbsp; ⇒ &nbsp; V_2(f) \equiv 0.
 +
<br clear=all>
 +
[[File:P_ID1614__Mod_Z_4_2e.png|P_ID1614__Mod_Z_4_2e.png|right|frame|Sampled harmonic oscillation with phase&nbsp; φ_3 = π/4]]
 +
'''(5)'''&nbsp; <u>None of the given solutions</u>&nbsp; is correct:
 +
*If in the graph for the subtask&nbsp; '''(1)'''&nbsp; the sampling frequency&nbsp; f_{\rm A} = 11 \ \rm kHz&nbsp; is replaced by&nbsp; f_{\rm A} = 10 \ \rm kHz,&nbsp; the real parts add up,&nbsp; but the imaginary parts cancel out.
 +
*This means that now&nbsp; Q_{\rm A}(f)&nbsp; and&nbsp; V_3(f)&nbsp; are real spectra.&nbsp; This further means:
 +
*The phase information is lost&nbsp; (φ = 0)&nbsp; and the output signal&nbsp; v_3(t)&nbsp; is a cosine signal.
 +
*q_3(t)&nbsp; and&nbsp; v_3(t)&nbsp; thus differ in both amplitude and phase.&nbsp; Only the frequency remains the same.
 +
 
 +
 
 +
The graph shows
 +
*turquoise the signal q_3(t)&nbsp; and its samples&nbsp; (circles),&nbsp; and
 +
*red dashed the output signal&nbsp; v_3(t)&nbsp; of the low-pass.
 +
 
 +
 
 +
You can see that the low-pass gives exactly the result you would probably choose if you were to draw a curve through the samples&nbsp; (circles).
 +
 
 +
 
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  
  
  
[[Category:Aufgaben zu  Modulationsverfahren|^4.1 Pulscodemodulation^]]
+
[[Category:Modulation Methods: Exercises|^4.1 Pulse Code Modulation^]]

Latest revision as of 12:28, 8 April 2022

Harmonic oscillations of different phase

The  sampling theorem  states that the sampling frequency  f_{\rm A} = 1/T_{\rm A}  must be at least twice as large as the largest frequency  f_\text {N, max}  contained in the source signal  q(t):

f_{\rm A} \ge 2 \cdot f_{\rm N,\hspace{0.05cm}max}\hspace{0.3cm}\Rightarrow \hspace{0.3cm} T_{\rm A} \le \frac{1}{2 \cdot f_{\rm N, \hspace{0.05cm}max}}\hspace{0.05cm}.

If this condition is met,  then at the receiver the message signal can be passed through a rectangular  (ideal)  low-pass filter with frequency response

H(f) = \left\{ \begin{array}{l} 1 \\ 1/2 \\ 0 \\ \end{array} \right.\quad \begin{array}{*{5}c}{\rm{f\ddot{u}r}} \\{\rm{f\ddot{u}r}} \\{\rm{f\ddot{u}r}} \\ \end{array}\begin{array}{*{10}c} {\hspace{0.04cm}\left| \hspace{0.005cm} f\hspace{0.05cm} \right| < f_{\rm G},} \\ {\hspace{0.04cm}\left| \hspace{0.005cm} f\hspace{0.05cm} \right| = f_{\rm G},} \\ {\hspace{0.04cm}\left| \hspace{0.005cm} f\hspace{0.05cm} \right| > f_{\rm G}} \\ \end{array}

can be completely reconstructed, that is, it is then  v(t) = q(t).

  • The cutoff frequency  f_{\rm G}  is to be chosen equal to half the sampling frequency.
  • The equal sign is generally valid only if the spectrum  Q(f)  does not contain a discrete spectral line at frequency  f_\text {N, max}.


In this exercise,  three different source signals are considered,  each of which can be expressed as a harmonic oscillation

q(t) = A \cdot \cos (2 \pi \cdot f_{\rm N} \cdot t - \varphi)

with amplitude  A = 1\ \rm V  and frequency  f_{\rm N}= 5 \ \rm kHz.  For the spectral function  Q(f)  of all represented time signals generally holds:

Q(f) = \frac{A}{2} \cdot \delta (f- f_{\rm N}) \cdot {\rm e}^{-{\rm j}\hspace{0.04cm}\cdot \hspace{0.04cm}\varphi}+ \frac{A}{2} \cdot \delta (f+ f_{\rm N}) \cdot {\rm e}^{+{\rm j}\hspace{0.04cm}\cdot \hspace{0.04cm}\varphi}\hspace{0.05cm}.

The oscillations sketched in the graph differ only by the phase  φ:

  • φ_1 = 0   ⇒   cosine signal  q_1(t),
  • φ_2 = π/2 \ (= 90^\circ)   ⇒   sinusoidal signal  q_2(t),
  • φ_3 = π/4 \ (= 45^\circ)   ⇒   signal  q_3(t).




Hints:

  • The exercise belongs to the chapter  "Pulse Code Modulation".
  • Reference is made in particular to the page  "Sampling and Signal Reconstruction".
  • The sampled source signal is denoted by  q_{\rm A}(t)  and its spectral function by  Q_{\rm A}(f)
  • Sampling is always performed at  ν \cdot T_{\rm A}.


Questions

1

Which statements are valid with  f_{\rm A} = 11\ \rm kHz?

The sampling theorem is always satisfied.
All signals can be reconstructed by a low-pass filter.
It is always true:  Q_{\rm A}(f = 5 \ {\rm kHz}) = Q(f = 5 \ \rm kHz).

2

What sampling distance results with  f_{\rm A} = 10\ \rm kHz?

T_{\rm A} \ = \

\ \rm ms

3

Which statements are valid for the signal  q_1(t)  and  f_{\rm A} = 10\ \rm kHz?

It holds  Q_{\rm A}(f = 5 \ {\rm kHz)} = Q_1(f = 5 \ \rm kHz).
A complete signal reconstruction is possible   ⇒   v_1(t) = q_1(t).
The reconstructed signal is  v_1(t) \equiv 0.

4

What statements hold for the signal  q_2(t)  and  f_{\rm A} = 10\ \rm kHz?

It holds  Q_{\rm A}(f = 5 \ {\rm kHz)} = Q_2(f = 5 \ \rm kHz).
A complete signal reconstruction is possible   ⇒   v_2(t) = q_2(t).
The reconstructed signal is  v_2(t) \equiv 0.

5

What statements hold for the signal  q_3(t) and f_{\rm A} = 10\ \rm kHz?

It holds  Q_{\rm A}(f = 5 \ {\rm kHz)} = Q_3(f = 5 \ \rm kHz).
A complete signal reconstruction is possible   ⇒   v_3(t) = q_3(t).
The reconstructed signal is  v_3(t) \equiv 0.


Solution

(1)  All statements  are true:

Spectral function of the sampled signal
  • The sampling theorem is satisfied by  f_{\rm A} = 11 \ \rm kHz > 2 \cdot 5 \ \rm kHz  so that a complete signal reconstruction is always possible.
  • The spectrum  Q_{\rm A}(f)  results from  Q(f)  by periodic continuation at the respective frequency spacing  f_{\rm A},  which is generally illustrated in the graph.
  • By a rectangular low-pass with  f_{\rm G} = f_{\rm A}/2 = 5.5 \ \rm kHz  the original spectrum  Q(f) is obtained.


The shift by

  • f_{\rm A} = 11 \ \rm kHz  yields the lines at  +6 \ \rm kHz  and  +16 \ \rm kHz,
  • -f_{\rm A} = -11 \ \rm kHz  yields the lines at  -6 \ \rm kHz  and  -16 \ \rm kHz,
  • 2 - f_{\rm A} = 22 \ \rm kHz  yields the lines at  +17 \ \rm kHz  and  +27 \ \rm kHz,
  • -2 - f_{\rm A}= -22 \ \rm kHz  yields the lines at  -17 \ \rm kHz, -27 \ \rm kHz.


(2)  The sampling distance is equal to the reciprocal of the sampling frequency:

T_{\rm A} = {1}/{f_{\rm A} }\hspace{0.15cm}\underline { = 0.1\,{\rm ms}} \hspace{0.05cm}.


(3)  The correct solution is  suggestion 2:

Spectral function of the sampled cosine signal
  • For the cosinusoidal signal,  according to this graph with  f_{\rm A} = 10 \rm \ kHz:  All spectral lines of  Q_{\rm A}(f):  are real.
  • The periodization of  Q(f)  with  f_{\rm A} = 10 \rm \ kHz  leads to a Dirac comb with spectral lines at  ±f_{\rm N}±f_{\rm N}± f_{\rm A}±f_{\rm N}± 2f_{\rm A}, . ..
  • Through the superpositions,  all Dirac functions have weight  A,  while the spectral lines of  Q(f)  are weighted only by  A/2  each.
  • Because  H(f = f_{\rm N}) = H(f = f_{\rm G}) = 0.5  the spectrum  V_1(f)  after the low-pass is identical to  Q_1(f)   ⇒   v_1(t) = q_1(t).
  • In the time domain, the signal reconstruction can be thought of as follows:   The samples of  q_1(t)  lie exactly at the signal maxima and minima.  
  • The lowpass filter forms the cosine signal with correct amplitude, frequency and phase.


Sampled sine signal

(4)  Correct is  suggested solution 2:

  • All sampled values of  q_2(t)  now lie exactly at the zero crossings of the sinusoidal signal,  which means that here  q_{\rm A}(t) \equiv 0  holds.  However,  this naturally also gives  v_2(t) \equiv 0.
  • In the spectral domain,  the result can be derived using the graph for subtask  (1)
    ⇒  Q(f)  is purely imaginary and the imaginary parts at  ±f_{\rm N}  have different signs.  
  • Thus,  one positive and one negative part cancel each other in periodization  
    ⇒   Q_{\rm A}(f) \equiv 0   ⇒   V_2(f) \equiv 0.


Sampled harmonic oscillation with phase  φ_3 = π/4

(5)  None of the given solutions  is correct:

  • If in the graph for the subtask  (1)  the sampling frequency  f_{\rm A} = 11 \ \rm kHz  is replaced by  f_{\rm A} = 10 \ \rm kHz,  the real parts add up,  but the imaginary parts cancel out.
  • This means that now  Q_{\rm A}(f)  and  V_3(f)  are real spectra.  This further means:
  • The phase information is lost  (φ = 0)  and the output signal  v_3(t)  is a cosine signal.
  • q_3(t)  and  v_3(t)  thus differ in both amplitude and phase.  Only the frequency remains the same.


The graph shows

  • turquoise the signal q_3(t)  and its samples  (circles),  and
  • red dashed the output signal  v_3(t)  of the low-pass.


You can see that the low-pass gives exactly the result you would probably choose if you were to draw a curve through the samples  (circles).