Difference between revisions of "Aufgaben:Exercise 4.12: Power-Spectral Density of a Binary Signal"

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{{quiz-Header|Buchseite=Theory_of_Stochastic_Signals/Power-Spectral_Density
 
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[[File:P_ID405__Sto_A_4_12.png|right|]]
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[[File:P_ID405__Sto_A_4_12.png|right|300px|frame|Binary square-wave signals]]
:Wir betrachten ein rechteckf&ouml;rmiges Bin&auml;rsignal <i>x</i>(<i>t</i>) mit gleichwahrscheinlichen Amplitudenwerten +2V und -2V. Die Symboldauer betr&auml;gt <i>T</i> = 1 &mu;s. In Aufgabe A4.10 wurde bereits gezeigt, dass die dazugeh&ouml;rige AKF auf den Bereich von -<i>T</i> &#8804; <i>&tau;</i> &#8804; <i>T</i> beschr&auml;nkt ist und in diesem Bereich dreieckf&ouml;rmig verl&auml;uft:
+
We consider a rectangular binary signal&nbsp; $x(t)$&nbsp; with equal probability amplitude values&nbsp; $+2\hspace{0.05cm}\rm V$&nbsp; and&nbsp; $-2\hspace{0.05cm}\rm V$.
:$$\varphi_x (\tau) = {\rm 4 \hspace{0.05cm}V^2} \cdot (1 - \frac{| \tau |}{T}).$$
+
*The symbol duration is&nbsp; $T = 1 \hspace{0.05cm}\rm &micro; s$.  
 +
*In&nbsp; [[Aufgaben:Exercise_4.10:_Binary_and_Quaternary|Exercise 4.10]]&nbsp; it has already been shown that the associated ACF is restricted to the range of&nbsp; $-T \le \tau\le +T$&nbsp; and is triangular in this range:
 +
:$$\varphi_x (\tau) = 4 \hspace{0.05cm}{\rm V}^2 \cdot (1 - | \tau |/{T}).$$
  
:Hierbei ist vorausgesetzt, dass die einzelnen Symbole statistisch voneinander unabh&auml;ngig sind.  
+
*It is assumed here that the individual symbols are statistically independent of each other.  
  
:Das unten skizzierte Signal <i>y</i>(<i>t</i>) ist ebenfalls bin&auml;r und rechteckf&ouml;rmig mit der gleichen Symboldauer <i>T</i> = 1 &mu;s. Die m&ouml;glichen Amplitudenwerte sind nun aber 0V und 4V, wobei der Amplitudenwert 4V seltener als der Wert 0V auftritt. Es gilt:
 
:$${\rm Pr}(x(t) = 4 \hspace{0.05cm} {\rm V}) = p\hspace{0.5cm} {\rm mit}\hspace{0.5cm} 0 <p \le 0.25.$$
 
  
:<b>Hinweis</b>: Diese Aufgabe bezieht sich auf den Theorieteil von Kapitel 4.5. Beachten Sie die folgende Fourierkorrespondenz:
+
The signal&nbsp; $y(t)$&nbsp; sketched below is also binary and rectangular with the same symbol duration&nbsp; $T = 1 \hspace{0.05cm}\rm &micro; s$.
:$${\rm \Delta} (t) \hspace{0.3cm} \circ\!\!-\!\!\!-\!\!\!-\!\!\bullet\, \hspace{0.3cm} T \cdot {\rm si}^2 ( \pi f T).$$
+
*But the possible amplitude values are now&nbsp; $0\hspace{0.05cm}\rm V$&nbsp; and&nbsp; $4\hspace{0.05cm}\rm V$.
 +
* The amplitude value&nbsp; $4\hspace{0.05cm}\rm V$&nbsp; occurs less frequently than&nbsp; $0\hspace{0.05cm}\rm V$. It holds:
 +
:$${\rm Pr}(x(t) = 4 \hspace{0.05cm} {\rm V}) = p\hspace{0.5cm} {\rm with}\hspace{0.5cm} 0 < p \le 0.25.$$
  
:Dabei bezeichnet &Delta;(<i>t</i>) einen um <i>t</i> = 0 symmetrischen Dreieckimpuls mit &Delta;(0) = 1 und &Delta;(<i>t</i>) = 0 f&uuml;r |<i>t</i>| &#8805; <i>T</i>. Weiterhin gilt die Notation si(<i>x</i>) = sin(<i>x</i>)/<i>x</i> mit folgendem Integralwert:
 
:$$\int^1_0 {\rm si}^2 ( \pi u) \, {\rm d}u \ \approx 0.456.$$
 
  
  
===Fragebogen===
+
 
 +
 
 +
 
 +
 
 +
 
 +
 
 +
 
 +
Hints:
 +
*This exercise belongs to the chapter&nbsp; [[Theory_of_Stochastic_Signals/Power-Spectral_Density|Power-Spectral Density]].
 +
 +
*Note the following Fourier correspondence, where&nbsp; ${\rm \Delta} (t)$&nbsp; a triangular pulse symmetric about&nbsp; $t= 0$&nbsp; with&nbsp; ${\rm \Delta} (t= 0) = 1$&nbsp; and&nbsp; ${\rm \Delta} (t) = 0$&nbsp; for&nbsp; $|t| \ge T$&nbsp; denotes:
 +
:$${\rm \Delta} (t) \hspace{0.3cm} \circ\!\!\!\!\!\!\!\!\bullet\, \hspace{0.3cm} T \cdot {\rm si}^2 ( \pi f T).$$
 +
*Further, the notation&nbsp; ${\rm si}(x) = \sin(x)/x$&nbsp; holds with the following integral value:
 +
:$$\int^1_0 {\rm si}^2 ( \pi \cdot u) \, {\rm d}u \ \approx 0.456.$$
 +
 
 +
 
 +
 
 +
 
 +
===Questions===
  
 
<quiz display=simple>
 
<quiz display=simple>
{Geben Sie das Leistungsdichtespektrum <i>&Phi;<sub>x</sub></i>(<i>f</i>) des bipolaren Zufallssignals <i>x</i>(<i>t</i>) an. Welche LDS-Werte ergeben sich f&uuml;r <i>f</i> = 0, <i>f</i> = 500 kHz, <i>f</i> = 1 MHz?
+
{Give the power-spectral density&nbsp; ${\it \Phi}_x(f)$&nbsp; of the bipolar random signal&nbsp; $x(t)$&nbsp; ;
 +
What PSD values result f&uuml;r&nbsp; $f= 0$,&nbsp; $f = 500 \hspace{0.05cm}\rm kHz$&nbsp; and&nbsp; $f = 1 \hspace{0.05cm}\rm MHz$?
 
|type="{}"}
 
|type="{}"}
$\phi_x(f = 0)$ = { 4 3% } $.10^-6 \ V^2 /Hz$
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${\it \Phi}_x(f = 0) \ = \ $ { 4 3% } $\ \cdot 10^{-6} \ \rm V^2 /Hz$
$\phi_x(f = 500 kHz)$ = { 1.62 3% } $.10^-6 \ V^2 /Hz$
+
${\it \Phi}_x(f = 500 \hspace{0.08cm}\rm kHz) \ = \ $ { 1.62 3% } $\ \cdot 10^{-6} \ \rm V^2 /Hz$
$\phi_x(f = 1 MHz)$ = { 0 3% } $V^2 /Hz$
+
${\it \Phi}_x(f = 1 \hspace{0.08cm}\rm MHz) \ = \ $ { 0. } $\ \cdot 10^{-6} \ \rm V^2 /Hz$
  
  
{Berechnen Sie die AKF <i>&phi;<sub>y</sub></i>(<i>&tau;</i>) des unipolaren Zufallssignals <i>y</i>(<i>t</i>). Welche AKF-Werte ergeben sich mit <i>p</i> = 0.25 f&uuml;r <i>&tau;</i> = 0, <i>&tau;</i> = <i>T</i> und <i>&tau;</i> = 2<i>T</i>?
+
{Calculate the ACF&nbsp; $\varphi_y(\tau)$&nbsp; of the unipolar random signal&nbsp; $y(t)$.&nbsp; What ACF values result with&nbsp; $p = 0.25$&nbsp; for&nbsp; $\tau =0$,&nbsp; $\tau =T$&nbsp; and&nbsp; $\tau =2T$&nbsp;?
 
|type="{}"}
 
|type="{}"}
<i>&phi;<sub>y</sub></i>(<i>&tau; = 0</i>) = { 4 3% } $V^2$
+
$\varphi_y(\tau = 0) \ = \ $ { 4 3% } $\ \rm V^2$
<i>&phi;<sub>y</sub></i>(<i>&tau; = T</i>) = { 1 3% } $V^2$
+
$\varphi_y(\tau = T) \ = \ $ { 1 3% } $\ \rm V^2$
<i>&phi;<sub>y</sub></i>(<i>&tau; = 2T</i>) = { 1 3% } $V^2$
+
$\varphi_y(\tau = 2T) \ = \ $ { 1 3% } $\ \rm V^2$
  
  
{Berechnen Sie das zugeh&ouml;rige Leistungsdichtespektrum <i>&Phi;<sub>y</sub></i>(<i>f</i>). Welcher Wert ergibt sich f&uuml;r <i>f</i> = 500 kHz?
+
{Calculate the associated power-spectral density&nbsp; ${\it \Phi}_y(f)$.&nbsp; What PSD value results f&uuml;r&nbsp; $f = 500 \hspace{0.05cm}\rm kHz$&nbsp;?
 
|type="{}"}
 
|type="{}"}
$\phi_y(f = 500 kHz)$ = { 1.216 3% } $.10^-6 \ V^2 /Hz$
+
${\it \Phi}_x(f = 500 \hspace{0.08cm}\rm kHz) \ = \ $ { 1.216 3% } $\ \cdot 10^{-6} \ \rm V^2 /Hz$
  
  
{Welche mittlere Signalleistung <i>P</i><sub>M</sub> (bezogen auf den Widerstand 1 &Omega;) zeigt ein Messger&auml;t an, das nur Leistungsanteile bis 1 MHz erfasst?
+
{What is the average signal power&nbsp; $P_{\rm M}$&nbsp; $($related to the resistor&nbsp; $1 \hspace{0.08cm}\rm \Omega)$&nbsp; displayed by a meter that only detects power components up to&nbsp; $1 \hspace{0.05cm}\rm MHz$&nbsp; ?
 
|type="{}"}
 
|type="{}"}
$P_M$ = { 3.736 3% } $V^2$
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$P_{\rm M} \ = \ $ { 3.736 3% } $\ \rm V^2$
 
 
  
  
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===Musterlösung===
 
===Musterlösung===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
[[File: P_ID406__Sto_A_4_12_a.png|right|]]
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[[File: P_ID406__Sto_A_4_12_a.png|right|frame|Power-spectral density with DC component]]
:<b>1.</b>&nbsp;&nbsp;Das LDS ist die Fouriertransformierte der AKF. Mit der Fourierkorrespondenz auf der Angabenseite und <i>x</i><sub>0</sub> = 2 V erh&auml;lt man:
+
'''(1)'''&nbsp; The PSD is the Fourier transform of the ACF.
 +
*With the Fourier correspondence on the data side and&nbsp; $x_0 = 2\hspace{0.05cm}\rm V$&nbsp; one obtains:
 
:$${\it \Phi}_x(f)= x_{\rm 0}^2 \cdot T \cdot {\rm si}^2(\pi f T).$$
 
:$${\it \Phi}_x(f)= x_{\rm 0}^2 \cdot T \cdot {\rm si}^2(\pi f T).$$
  
:Der LDS-Wert bei <i>f</i> = 0 ist <u>4 &middot; 10<sup>&ndash;6</sup> V<sup>2</sup>/Hz</u>. Bei <i>f</i> = 500 kHz ist das LDS um den Faktor si<sup>2</sup>(&pi;/2) = 4/&pi;<sup>2</sup> &asymp; 0.405 kleiner (<u>1.62 &middot; 10<sup>&ndash;6</sup> V<sup>2</sup>/Hz)</u>. Bei <i>f</i> = 1 MHz besitzt  <i>&Phi;<sub>x</sub></i>(<i>f</i>) <u>die erste Nullstelle</u>.
+
*The PSD values we are looking for are:  
[[File:P_ID407__Sto_A_4_12_b.png|right|]]
+
:$${\it \Phi}_x(f = 0)\hspace{0.15cm}\underline {=4} \cdot 10^{-6} \rm V^2 /Hz,$$
 +
:$${\it \Phi}_x(f = 500 \hspace{0.05cm}\rm kHz)\hspace{0.15cm}\underline {=1.62} \cdot 10^{-6} \rm V^2 /Hz,$$
 +
:$${\it \Phi}_x(f = 1 \hspace{0.05cm}\rm MHz)\hspace{0.15cm}\underline {=0}.$$
 +
*At&nbsp; $f = 1 \hspace{0.05cm}\rm MHz $&nbsp; the power-spectral density has the first zero.
  
:<b>2.</b>&nbsp;&nbsp;Aufgrund des rechteckigen Signalverlaufs &auml;ndert sich an der Dreiecksform der AKF prinzipiell nichts. Der AKF-Wert bei <i>&tau;</i> = 0 gibt wieder das Moment 2. Ordnung an. Mit <i>p</i> = 0.25 erh&auml;lt man:
 
:$$\varphi_y( 0) = \frac{1}{4}\cdot {(\rm 4V)}^2 + \frac{3}{4}\cdot {(\rm 0V)}^2 \hspace{0.15cm}\underline{= {\rm 4\,V^2}}.$$
 
  
:Ab <i>&tau;</i> = <i>T</i> ist die AKF konstant gleich <i>m<sub>y</sub></i><sup>2</sup>. Mit der Wahrscheinlichkeit <i>p</i> = 0.25 und
 
:$$m_y = p \cdot {\rm 4V} + (1-p)\cdot {\rm 0V} = 1 \, \rm V$$
 
  
:erh&auml;lt man ab <i>&tau;</i> = <i>T</i> den konstanten Wert <i>&phi;<sub>y</sub></i>(<i>&tau;</i> &#8805; <i>T</i>) = <u>1 V<sup>2</sup></u>.
+
[[File:P_ID407__Sto_A_4_12_b.png|right|frame|Auto-correlation function with DC component ]]
 +
'''(2)'''&nbsp; Due to the rectangular waveform, the triangular shape of the ACF does not change in principle.
 +
*The ACF value at&nbsp; $\tau = 0$&nbsp; again gives the second order moment.
 +
*With&nbsp; $p = 0.25$&nbsp; one obtains:
 +
:$$\varphi_y( 0) = {1}/{4}\cdot {(\rm 4\hspace{0.05cm}V)}^2 + {3}/{4}\cdot {(\rm 0\hspace{0.05cm}V)}^2 \hspace{0.15cm}\underline{= {\rm 4\,V^2}}.$$
  
:<b>3.</b>&nbsp;&nbsp;Die AKF kann auch wie folgt dargestellt werden:
+
*From&nbsp; $\tau =T$&nbsp; the ACF is constantly equal to&nbsp; $m_y^2$.
:$$\varphi_y(\tau) = 1{\rm V}^2 + 3 {\rm V}^2 \cdot \Delta (\tau).$$
+
*With probability&nbsp; $p = 0.25$&nbsp; and &nbsp;$m_y = p \cdot {\rm 4\hspace{0.05cm}V} + (1-p)\cdot {\rm 0\hspace{0.05cm}V} = 1 \, \rm V$&nbsp; obtains from&nbsp; $\tau =T$&nbsp; the constant value&nbsp; $\varphi_y( \tau >T) \hspace{0.15cm}\underline {=\rm 1\,V^2}$.
  
:Der AKF-Gleichanteil (mit 1V<sup>2</sup>) f&uuml;hrt im LDS zu einer Diracfunktion bei <i>f</i> = 0 (siehe Skizze zu a). Der dreieckf&ouml;rmige AKF-Term bewirkt einen kontinuierlichen LDS-Anteil entsprechend der si<sup>2</sup>-Form:
 
:$${\it \Phi}_y(f)= 1{\rm V}^2 \cdot {\rm \delta  } (f) + 3 \cdot 10^{-6} {\frac {\rm V^2} {\rm Hz}}  \cdot {\rm si}^2(\pi f T).$$
 
  
:F&uuml;r <i>f</i> = 500 kHz (<i>f</i> &middot; <i>T</i> = 0.5) ergibt sich der LDS-Wert zu <u>1.216 &middot; 10<sup>&ndash;6</sup> V<sup>2</sup>/Hz</u>.
 
  
:<b>4.</b>&nbsp;&nbsp;Die Leistung ist als Integral &uuml;ber das LDS berechenbar. Unter Ber&uuml;cksichtigung der spektralen Begrenzung auf 1 MHz erh&auml;lt man
+
'''(3)'''&nbsp; The ACF can also be represented as follows:
:mit der Substitution <i>u</i> = <i>f</i> &middot; <i>T</i> :
+
:$$\varphi_y(\tau) = 1\hspace{0.05cm}{\rm V}^2 + 3\hspace{0.05cm}{\rm V}^2 \cdot \Delta (\tau).$$
:$$P_{\rm M} \hspace{-0.15cm} = \hspace{-0.15cm} 1{\rm V}^2 + 3 \cdot 10^{-6} {\frac {\rm V^2} {\rm Hz}} \cdot \int^{\rm 1 MHz}_{-\rm 1 MHz} {\rm si}^2(\pi f T)\hspace{0.1cm}{\rm d}f = \\
 
=\hspace{-0.15cm} 1{\rm V}^2  + 3  V^2 \cdot 2 \cdot \int^{1}_{\rm 0} {\rm si}^2(\pi u)\hspace{0.1cm}{\rm d}u = (1 + 3\cdot 2 \cdot 0.456)\,{\rm V^2} \hspace{0.15cm}\underline{= 3.736 \, {\rm V^2}}. $$
 
  
:W&uuml;rden dagegen alle Spektralanteile erfasst, erg&auml;be sich die Leistung <i>&phi;<sub>y</sub></i>(<i>&tau;</i> = 0) = 4 V<sup>2</sup>.
+
*The ACF DC component&nbsp; $($with&nbsp; $1\hspace{0.05cm}{\rm V}^2)$&nbsp; leads to a Dirac function in the PSD at&nbsp; $f = 0$ &nbsp; &rArr; &nbsp; see sketch for subtask&nbsp; '''(1)'''.
 +
*The triangularf&ouml;rm ACF term causes a continuous PSD component corresponding to the&nbsp; $\rm si^2$-form:
 +
:$${\it \Phi}_y(f)= 1{\rm V}^2 \cdot {\rm \delta } (f) + 3 \cdot 10^{-6}\ {\rm V^2\hspace{-0.1cm}/Hz}  \cdot {\rm si}^2(\pi f T).$$
 +
*For&nbsp; $f = 500 \hspace{0.05cm}\rm kHz$ &nbsp; &rArr; &nbsp; $f \cdot T =0.5$&nbsp; the PSD value results to&nbsp; ${\underline {1.216}  \cdot 10^{-6} \rm V^2 /Hz}$.
 +
'''(4)'''&nbsp; The power can be calculated as an integral over the PSD.
 +
*Taking into account the spectral limitation to&nbsp; $ 1 \hspace{0.05cm}\rm MHz$&nbsp; one obtains with the substitution&nbsp; $u =f \cdot T$:
 +
:$$P_{\rm M} = 1{\rm V}^2 + 3 \cdot 10^{-6} {{\rm V^2} /{\rm Hz}} \cdot \int^{\rm 1 MHz}_{-\rm 1 MHz} {\rm si}^2(\pi f T)\hspace{0.1cm}{\rm d}f = 1{\rm V}^2 + 3 V^2 \cdot 2 \cdot \int^{1}_{\rm 0} {\rm si}^2(\pi u)\hspace{0.1cm}{\rm d}u = (1 + 3\cdot 2 \cdot 0.456)\,{\rm V^2} \hspace{0.15cm}\underline{= 3.736 \, {\rm V^2}}. $$
 +
*If, on the other hand, all spectral components were covered, the average power would result in&nbsp; $\varphi_y( \tau= 0) = 4 \, {\rm V^2}$.
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  
  
  
[[Category:Aufgaben zu Stochastische Signaltheorie|^4.5 Leistungsdichtespektrum (LDS)^]]
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[[Category:Theory of Stochastic Signals: Exercises|^4.5 Power-Spectral Density^]]

Latest revision as of 18:16, 7 March 2022

Binary square-wave signals

We consider a rectangular binary signal  $x(t)$  with equal probability amplitude values  $+2\hspace{0.05cm}\rm V$  and  $-2\hspace{0.05cm}\rm V$.

  • The symbol duration is  $T = 1 \hspace{0.05cm}\rm µ s$.
  • In  Exercise 4.10  it has already been shown that the associated ACF is restricted to the range of  $-T \le \tau\le +T$  and is triangular in this range:
$$\varphi_x (\tau) = 4 \hspace{0.05cm}{\rm V}^2 \cdot (1 - | \tau |/{T}).$$
  • It is assumed here that the individual symbols are statistically independent of each other.


The signal  $y(t)$  sketched below is also binary and rectangular with the same symbol duration  $T = 1 \hspace{0.05cm}\rm µ s$.

  • But the possible amplitude values are now  $0\hspace{0.05cm}\rm V$  and  $4\hspace{0.05cm}\rm V$.
  • The amplitude value  $4\hspace{0.05cm}\rm V$  occurs less frequently than  $0\hspace{0.05cm}\rm V$. It holds:
$${\rm Pr}(x(t) = 4 \hspace{0.05cm} {\rm V}) = p\hspace{0.5cm} {\rm with}\hspace{0.5cm} 0 < p \le 0.25.$$






Hints:

  • Note the following Fourier correspondence, where  ${\rm \Delta} (t)$  a triangular pulse symmetric about  $t= 0$  with  ${\rm \Delta} (t= 0) = 1$  and  ${\rm \Delta} (t) = 0$  for  $|t| \ge T$  denotes:
$${\rm \Delta} (t) \hspace{0.3cm} \circ\!\!\!\!\!\!\!\!\bullet\, \hspace{0.3cm} T \cdot {\rm si}^2 ( \pi f T).$$
  • Further, the notation  ${\rm si}(x) = \sin(x)/x$  holds with the following integral value:
$$\int^1_0 {\rm si}^2 ( \pi \cdot u) \, {\rm d}u \ \approx 0.456.$$



Questions

1

Give the power-spectral density  ${\it \Phi}_x(f)$  of the bipolar random signal  $x(t)$  ; What PSD values result für  $f= 0$,  $f = 500 \hspace{0.05cm}\rm kHz$  and  $f = 1 \hspace{0.05cm}\rm MHz$?

${\it \Phi}_x(f = 0) \ = \ $

$\ \cdot 10^{-6} \ \rm V^2 /Hz$
${\it \Phi}_x(f = 500 \hspace{0.08cm}\rm kHz) \ = \ $

$\ \cdot 10^{-6} \ \rm V^2 /Hz$
${\it \Phi}_x(f = 1 \hspace{0.08cm}\rm MHz) \ = \ $

$\ \cdot 10^{-6} \ \rm V^2 /Hz$

2

Calculate the ACF  $\varphi_y(\tau)$  of the unipolar random signal  $y(t)$.  What ACF values result with  $p = 0.25$  for  $\tau =0$,  $\tau =T$  and  $\tau =2T$ ?

$\varphi_y(\tau = 0) \ = \ $

$\ \rm V^2$
$\varphi_y(\tau = T) \ = \ $

$\ \rm V^2$
$\varphi_y(\tau = 2T) \ = \ $

$\ \rm V^2$

3

Calculate the associated power-spectral density  ${\it \Phi}_y(f)$.  What PSD value results für  $f = 500 \hspace{0.05cm}\rm kHz$ ?

${\it \Phi}_x(f = 500 \hspace{0.08cm}\rm kHz) \ = \ $

$\ \cdot 10^{-6} \ \rm V^2 /Hz$

4

What is the average signal power  $P_{\rm M}$  $($related to the resistor  $1 \hspace{0.08cm}\rm \Omega)$  displayed by a meter that only detects power components up to  $1 \hspace{0.05cm}\rm MHz$  ?

$P_{\rm M} \ = \ $

$\ \rm V^2$


Musterlösung

Power-spectral density with DC component

(1)  The PSD is the Fourier transform of the ACF.

  • With the Fourier correspondence on the data side and  $x_0 = 2\hspace{0.05cm}\rm V$  one obtains:
$${\it \Phi}_x(f)= x_{\rm 0}^2 \cdot T \cdot {\rm si}^2(\pi f T).$$
  • The PSD values we are looking for are:
$${\it \Phi}_x(f = 0)\hspace{0.15cm}\underline {=4} \cdot 10^{-6} \rm V^2 /Hz,$$
$${\it \Phi}_x(f = 500 \hspace{0.05cm}\rm kHz)\hspace{0.15cm}\underline {=1.62} \cdot 10^{-6} \rm V^2 /Hz,$$
$${\it \Phi}_x(f = 1 \hspace{0.05cm}\rm MHz)\hspace{0.15cm}\underline {=0}.$$
  • At  $f = 1 \hspace{0.05cm}\rm MHz $  the power-spectral density has the first zero.


Auto-correlation function with DC component

(2)  Due to the rectangular waveform, the triangular shape of the ACF does not change in principle.

  • The ACF value at  $\tau = 0$  again gives the second order moment.
  • With  $p = 0.25$  one obtains:
$$\varphi_y( 0) = {1}/{4}\cdot {(\rm 4\hspace{0.05cm}V)}^2 + {3}/{4}\cdot {(\rm 0\hspace{0.05cm}V)}^2 \hspace{0.15cm}\underline{= {\rm 4\,V^2}}.$$
  • From  $\tau =T$  the ACF is constantly equal to  $m_y^2$.
  • With probability  $p = 0.25$  and  $m_y = p \cdot {\rm 4\hspace{0.05cm}V} + (1-p)\cdot {\rm 0\hspace{0.05cm}V} = 1 \, \rm V$  obtains from  $\tau =T$  the constant value  $\varphi_y( \tau >T) \hspace{0.15cm}\underline {=\rm 1\,V^2}$.


(3)  The ACF can also be represented as follows:

$$\varphi_y(\tau) = 1\hspace{0.05cm}{\rm V}^2 + 3\hspace{0.05cm}{\rm V}^2 \cdot \Delta (\tau).$$
  • The ACF DC component  $($with  $1\hspace{0.05cm}{\rm V}^2)$  leads to a Dirac function in the PSD at  $f = 0$   ⇒   see sketch for subtask  (1).
  • The triangularförm ACF term causes a continuous PSD component corresponding to the  $\rm si^2$-form:
$${\it \Phi}_y(f)= 1{\rm V}^2 \cdot {\rm \delta } (f) + 3 \cdot 10^{-6}\ {\rm V^2\hspace{-0.1cm}/Hz} \cdot {\rm si}^2(\pi f T).$$
  • For  $f = 500 \hspace{0.05cm}\rm kHz$   ⇒   $f \cdot T =0.5$  the PSD value results to  ${\underline {1.216} \cdot 10^{-6} \rm V^2 /Hz}$.

(4)  The power can be calculated as an integral over the PSD.

  • Taking into account the spectral limitation to  $ 1 \hspace{0.05cm}\rm MHz$  one obtains with the substitution  $u =f \cdot T$:
$$P_{\rm M} = 1{\rm V}^2 + 3 \cdot 10^{-6} {{\rm V^2} /{\rm Hz}} \cdot \int^{\rm 1 MHz}_{-\rm 1 MHz} {\rm si}^2(\pi f T)\hspace{0.1cm}{\rm d}f = 1{\rm V}^2 + 3 V^2 \cdot 2 \cdot \int^{1}_{\rm 0} {\rm si}^2(\pi u)\hspace{0.1cm}{\rm d}u = (1 + 3\cdot 2 \cdot 0.456)\,{\rm V^2} \hspace{0.15cm}\underline{= 3.736 \, {\rm V^2}}. $$
  • If, on the other hand, all spectral components were covered, the average power would result in  $\varphi_y( \tau= 0) = 4 \, {\rm V^2}$.