Difference between revisions of "Aufgaben:Exercise 5.2Z: About PN Modulation"

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{{quiz-Header|Buchseite=Modualtionsverfahren/PN–Modulation
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{{quiz-Header|Buchseite=Modulation_Methods/Direct-Sequence_Spread_Spectrum_Modulation
 
}}
 
}}
  
[[File:P_ID1871__Mod_Z_5_2.png|right|]]
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[[File:EN_Bei_A_4_5.png|right|frame|Models of PN modulation (top) and BPSK (bottom)]]
Die Grafik zeigt das Ersatzschaltbild der PN–Modulation (''engl. Direct Sequence Spread Spectrum'', abgekürzt DS–SS) im äquivalenten Tiefpassbereich, wobei AWGN–Rauschen $n(t)$ zugrunde liegt. Darunter dargestellt ist das TP–Modell der binären Phasenmodulation (BPSK). Das Tiefpass–Sendesignal $s(t)$ ist aus Gründen einheitlicher Darstellung gleich dem rechteckförmigen Quellensignal $q(t)$ ∈ {+1, –1} mit Rechteckdauer T gesetzt ist. Die Funktion des Integrators kann wie folgt beschrieben werden:
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The upper diagram shows the equivalent circuit of  $\rm PN$  modulation  $($Direct-Sequence Spread Spectrum, abbreviated  $\rm DS–SS)$  in the equivalent low-pass range,  based on AWGN noise  $n(t)$. 
$$d (\nu T) = \frac{1}{T} \cdot \hspace{-0.1cm} \int_{(\nu -1 )T }^{\nu T} \hspace{-0.3cm} b (t )\hspace{0.1cm} {\rm d}t \hspace{0.05cm}.$$
 
Die beiden Modelle unterscheiden sich durch die Multiplikation mit dem ±1–Spreizsignal $c(t)$ bei Sender und Empfänger, wobei von $c(t)$ lediglich der Spreizgrad J bekannt ist. Für die Lösung dieser Aufgabe ist die Angabe der spezifischen Spreizfolge (M–Sequenz oder Walsh–Funktion) nicht von Bedeutung.
 
  
Zu untersuchen ist, ob sich das untere BPSK–Modell auch bei PN–Modulation anwenden lässt und ob die BPSK–Fehlerwahrscheinlichkeit
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Shown below is the low-pass model of binary phase shift keying  $\rm (BPSK)$. 
$$p_{\rm B} = {\rm Q} \left( \hspace{-0.05cm} \sqrt { \frac{2 \cdot E_{\rm B}}{N_{\rm 0}} } \hspace{0.05cm} \right )$$
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*The low-pass transmitted signal  $s(t)$  is set equal to the rectangular source signal  $q(t) ∈ \{+1, –1\}$  with rectangular duration  $T$  for reasons of uniformity.
auch für die PN–Modulation gültig ist, bzw. wie die angegebene Gleichung zu modifizieren ist.
 
  
'''Hinweis:''' Die Aufgabe gehört zum [http://en.lntwww.de/Modulationsverfahren/PN%E2%80%93Modulation Kapitel 5.2].  
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*The function of the integrator can be described as follows:
===Fragebogen===
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:$$d (\nu T) = \frac{1}{T} \cdot \hspace{-0.1cm} \int_{(\nu -1 )T }^{\nu T} \hspace{-0.3cm} b (t )\hspace{0.1cm} {\rm d}t \hspace{0.05cm}.$$
 +
 
 +
*The two models differ by multiplication with the  $±1$ spreading signal  $c(t)$  at transmitter and receiver,  where only the spreading factor  $J$  is known from  $c(t)$. 
 +
 
 +
 
 +
It has to be investigated whether the lower BPSK model can also be used for PN modulation and whether the BPSK error probability
 +
:$$p_{\rm B} = {\rm Q} \left( \hspace{-0.05cm} \sqrt { {2 \cdot E_{\rm B}}/{N_{\rm 0}} } \hspace{0.05cm} \right )$$
 +
is also valid for PN modulation,  or how the given equation should be modified.
 +
 
 +
 
 +
 
 +
 
 +
 
 +
Notes:
 +
*This exercise belongs to the chapter  [[Modulation_Methods/Direct-Sequence_Spread_Spectrum_Modulation|Direct-Sequence Spread Spectrum Modulation]].
 +
 
 +
*For the solution of this exercise,  the specification of the specific spreading sequence  $($M-sequence or Walsh function$)$  is not important.
 +
 +
 
 +
===Questions===
  
 
<quiz display=simple>
 
<quiz display=simple>
{Welche Detektionssignalwerte sind bei BPSK möglich (ohne Rauschen)?
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{Which detection signal values are possible with BPSK&nbsp; (in the noise-free case)?
 
|type="[]"}
 
|type="[]"}
- $d(νT)$ ist gaußverteilt.
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- $d(νT)$&nbsp; can be Gaussian distributed.
- $d(νT)$ kann die Werte +1, 0 und –1 annehmen.
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- $d(νT)$&nbsp; can take the values &nbsp;$+1$, &nbsp;$0$&nbsp; and &nbsp;$-1$.&nbsp;
+ Es sind nur die Werte $d(νT) = +1$ und $d(νT) = –1$ möglich.
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+ Only the values &nbsp;$d(νT) = +1$&nbsp; and &nbsp;$d(νT) = -1$&nbsp; are possible.
  
{Welche Werte sind bei PN–Modulation im rauschfreien Fall möglich?
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{Which values are possible in PN modulation&nbsp; (in the noise-free)&nbsp; case?
 
|type="[]"}
 
|type="[]"}
- $d(νT)$ ist gaußverteilt.
+
- $d(νT)$&nbsp; can be Gaussian distributed.
- $d(νT)$ kann die Werte +1, 0 und –1 annehmen.
+
- $d(νT)$&nbsp; can take the values &nbsp;$+1$, &nbsp;$0$&nbsp; and &nbsp;$-1$.&nbsp;
+ Es sind nur die Werte $d(νT) = +1$ und $d(νT) = –1$ möglich.
+
+ Only the values &nbsp;$d(νT) = +1$&nbsp; and &nbsp;$d(νT) = -1$&nbsp; are possible.
  
{Welche Modifikation muss am BPSK–Modell vorgenommen werden, damit es auch für die PN–Modulation anwendbar ist?
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{What modification must be made to the BPSK model to make it applicable to PN modulation?
 
|type="[]"}
 
|type="[]"}
+ Das Rauschen n(t) muss durch $n'(t) = n(t) · c(t)$ ersetzt werden.
+
+ The noise &nbsp;$n(t)$&nbsp; must be replaced by &nbsp;$n'(t) = n(t) · c(t)$.&nbsp;
- Die Integration muss nun über J · T erfolgen.
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- The integration must now be done over &nbsp;$J · T$.&nbsp;
- Die Rauschleistung $σ_n^2$ muss um den Faktor J vermindert werden.
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- The noise power &nbsp;$σ_n^2$&nbsp; must be reduced by a factor of &nbsp;$J$.&nbsp;
  
{Welche Bitfehlerwahrscheinlichkeit $p_B$ ergibt sich für $10 lg · (E_B/N_0) = 6 dB$ bei PN–Modulation? Bei BPSK gilt in diesem Fall: $p_B ≈ 2.3 · 10^{–3}$.
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{What is the bit error probability &nbsp;$p_{\rm B}$&nbsp; for &nbsp;$10 \lg (E_{\rm B}/N_0) = 6\ \rm  dB$&nbsp; for PN modulation?&nbsp; <br>Note: &nbsp; For BPSK, the following applies in this case: &nbsp; $p_{\rm B} ≈ 2.3 · 10^{–3}$.
|type="[]"}
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|type="()"}
- Je größer J gewählt wird, desto kleiner ist $p_B$.
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- The larger &nbsp;$J$&nbsp; is chosen, the smaller &nbsp;$p_{\rm B}$ is.
- Je größer J gewählt wird, desto größer ist $p_B$.
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- The larger &nbsp;$J$&nbsp; is chosen, the larger &nbsp;$p_{\rm B}$ is.
+ Es ergibt sich unabhängig von J stets der Wert $2.3 · 10^{–3}$.
+
+ Independent of &nbsp;$J$,&nbsp; the value &nbsp;$p_{\rm B} ≈ 2.3 · 10^{–3}$ is always obtained.
 
</quiz>
 
</quiz>
  
===Musterlösung===
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===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''1.'''
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'''(1)'''&nbsp; The&nbsp; <u>last solution</u>&nbsp; is correct:
'''2.'''
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*We are dealing here with an optimal receiver.
'''3.'''
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*Without noise,&nbsp; the signal&nbsp; $b(t)$&nbsp; within each bit is constantly equal to&nbsp; $+1$&nbsp; or&nbsp; $-1$.
'''4.'''
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*From the given equation for the integrator
'''5.'''
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:$$d (\nu T) = \frac{1}{T} \cdot \hspace{-0.1cm} \int_{(\nu -1 )T }^{\nu T} \hspace{-0.3cm} b (t )\hspace{0.1cm} {\rm d}t $$
'''6.'''
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:it follows that&nbsp; $d(νT)$&nbsp; can take only the values&nbsp; $+1$&nbsp; and&nbsp; $-1$.&nbsp;
'''7.'''
+
 
 +
 
 +
 
 +
'''(2)'''&nbsp; Again the&nbsp; <u>last solution</u>&nbsp; is correct:
 +
* In the noise-free and interference-free case &nbsp; ⇒ &nbsp; $n(t) = 0$,&nbsp; the twofold multiplication by&nbsp; $c(t) ∈ \{+1, –1\}$&nbsp; can be omitted,
 +
*so that the upper model is identical to the lower model.
 +
 
 +
 
 +
 
 +
'''(3)'''&nbsp; <u>Solution 1</u>&nbsp; is correct:
 +
*Since both models are identical in the noise-free case,&nbsp; only the noise signal has to be adjusted: &nbsp; $n'(t) = n(t) · c(t)$.
 +
*In contrast,&nbsp; the other two solutions are not applicable:
 +
*The integration must still be done over&nbsp; $T = J · T_c$&nbsp; and the PN modulation does not reduce the AWGN noise.
 +
 
 +
 
 +
 
 +
'''(4)'''&nbsp; The&nbsp; <u>last solution</u>&nbsp; is correct:
 +
*Multiplying the AWGN noise by the high-frequency&nbsp; $±1$ signal&nbsp; $c(t)$,&nbsp; the product is also Gaussian and white.
 +
*Because of &nbsp;${\rm E}\big[c^2(t)\big] = 1$,&nbsp; the noise variance is not changed either.&nbsp; Thus:                                                           
 +
*The equation&nbsp; $p_{\rm B} = {\rm Q} \left( \hspace{-0.05cm} \sqrt {{2 E_{\rm B}}/{N_{\rm 0}} } \hspace{0.05cm} \right )$&nbsp; valid for BPSK is also applicable for PN modulation,&nbsp; independent of spreading factor&nbsp; $J$&nbsp; and specific spreading sequence.
 +
*Ergo:&nbsp; For AWGN noise,&nbsp; band spreading neither increases nor decreases the error probability.
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  
  
  
[[Category:Aufgaben zu Modulationsverfahren|^5.2 PN–Modulation^]]
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[[Category:Modulation Methods: Exercises|^5.2 PN Modulation^]]

Latest revision as of 17:55, 4 March 2023

Models of PN modulation (top) and BPSK (bottom)

The upper diagram shows the equivalent circuit of  $\rm PN$  modulation  $($Direct-Sequence Spread Spectrum, abbreviated  $\rm DS–SS)$  in the equivalent low-pass range,  based on AWGN noise  $n(t)$. 

Shown below is the low-pass model of binary phase shift keying  $\rm (BPSK)$. 

  • The low-pass transmitted signal  $s(t)$  is set equal to the rectangular source signal  $q(t) ∈ \{+1, –1\}$  with rectangular duration  $T$  for reasons of uniformity.
  • The function of the integrator can be described as follows:
$$d (\nu T) = \frac{1}{T} \cdot \hspace{-0.1cm} \int_{(\nu -1 )T }^{\nu T} \hspace{-0.3cm} b (t )\hspace{0.1cm} {\rm d}t \hspace{0.05cm}.$$
  • The two models differ by multiplication with the  $±1$ spreading signal  $c(t)$  at transmitter and receiver,  where only the spreading factor  $J$  is known from  $c(t)$. 


It has to be investigated whether the lower BPSK model can also be used for PN modulation and whether the BPSK error probability

$$p_{\rm B} = {\rm Q} \left( \hspace{-0.05cm} \sqrt { {2 \cdot E_{\rm B}}/{N_{\rm 0}} } \hspace{0.05cm} \right )$$

is also valid for PN modulation,  or how the given equation should be modified.



Notes:

  • For the solution of this exercise,  the specification of the specific spreading sequence  $($M-sequence or Walsh function$)$  is not important.


Questions

1

Which detection signal values are possible with BPSK  (in the noise-free case)?

$d(νT)$  can be Gaussian distributed.
$d(νT)$  can take the values  $+1$,  $0$  and  $-1$. 
Only the values  $d(νT) = +1$  and  $d(νT) = -1$  are possible.

2

Which values are possible in PN modulation  (in the noise-free)  case?

$d(νT)$  can be Gaussian distributed.
$d(νT)$  can take the values  $+1$,  $0$  and  $-1$. 
Only the values  $d(νT) = +1$  and  $d(νT) = -1$  are possible.

3

What modification must be made to the BPSK model to make it applicable to PN modulation?

The noise  $n(t)$  must be replaced by  $n'(t) = n(t) · c(t)$. 
The integration must now be done over  $J · T$. 
The noise power  $σ_n^2$  must be reduced by a factor of  $J$. 

4

What is the bit error probability  $p_{\rm B}$  for  $10 \lg \ (E_{\rm B}/N_0) = 6\ \rm dB$  for PN modulation? 
Note:   For BPSK, the following applies in this case:   $p_{\rm B} ≈ 2.3 · 10^{–3}$.

The larger  $J$  is chosen, the smaller  $p_{\rm B}$ is.
The larger  $J$  is chosen, the larger  $p_{\rm B}$ is.
Independent of  $J$,  the value  $p_{\rm B} ≈ 2.3 · 10^{–3}$ is always obtained.


Solution

(1)  The  last solution  is correct:

  • We are dealing here with an optimal receiver.
  • Without noise,  the signal  $b(t)$  within each bit is constantly equal to  $+1$  or  $-1$.
  • From the given equation for the integrator
$$d (\nu T) = \frac{1}{T} \cdot \hspace{-0.1cm} \int_{(\nu -1 )T }^{\nu T} \hspace{-0.3cm} b (t )\hspace{0.1cm} {\rm d}t $$
it follows that  $d(νT)$  can take only the values  $+1$  and  $-1$. 


(2)  Again the  last solution  is correct:

  • In the noise-free and interference-free case   ⇒   $n(t) = 0$,  the twofold multiplication by  $c(t) ∈ \{+1, –1\}$  can be omitted,
  • so that the upper model is identical to the lower model.


(3)  Solution 1  is correct:

  • Since both models are identical in the noise-free case,  only the noise signal has to be adjusted:   $n'(t) = n(t) · c(t)$.
  • In contrast,  the other two solutions are not applicable:
  • The integration must still be done over  $T = J · T_c$  and the PN modulation does not reduce the AWGN noise.


(4)  The  last solution  is correct:

  • Multiplying the AWGN noise by the high-frequency  $±1$ signal  $c(t)$,  the product is also Gaussian and white.
  • Because of  ${\rm E}\big[c^2(t)\big] = 1$,  the noise variance is not changed either.  Thus:
  • The equation  $p_{\rm B} = {\rm Q} \left( \hspace{-0.05cm} \sqrt {{2 E_{\rm B}}/{N_{\rm 0}} } \hspace{0.05cm} \right )$  valid for BPSK is also applicable for PN modulation,  independent of spreading factor  $J$  and specific spreading sequence.
  • Ergo:  For AWGN noise,  band spreading neither increases nor decreases the error probability.