Difference between revisions of "Aufgaben:Exercise 3.12: Trellis Diagram for Two Precursors"

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{{quiz-Header|Buchseite=Digitalsignalübertragung/Viterbi–Empfänger}}
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{{quiz-Header|Buchseite=Digital_Signal_Transmission/Viterbi_Receiver}}
  
[[File:P_ID1478__Dig_A_3_12.png|right|frame|Trellisdiagramm für 2 Vorläufer]]
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[[File:P_ID1478__Dig_A_3_12.png|right|frame|Trellis diagram for two precursors]]
Wir gehen von den Grundimpulswerten $g_0$, $g_{\rm –1}$ und $g_{\rm –2}$ aus. Das bedeutet, dass die Entscheidung über das Symbol $a_{\rm \nu}$ auch durch die nachfolgenden Koeffizienten $a_{\rm \nu +1}$ und $a_{\rm \nu +2}$ beeinflusst wird. Damit sind für jeden Zeitpunkt $\nu$ genau $8$ Fehlergrößen $\epsilon_{\rm \nu}$ zu berechnen, aus denen die minimalen Gesamtfehlergrößen ${\it \Gamma}_{\rm \nu}(00)$, ${\it \Gamma}_{\rm \nu}(01)$, ${\it \Gamma}_{\rm \nu}(10)$ und ${\it \Gamma}_{\rm \nu}(11)$ berechnet werden können. Hierbei liefert beispielsweise ${\it \Gamma}_{\rm \nu}(01)$ Information über das Symbol $a_{\rm \nu}$ unter der Annahme, dass $a_{\rm \nu +1} = 0$ und $a_{\rm \nu +2} = 1$ sein werden. Die minimale Gesamtfehlergröße ${\it \Gamma}_{\rm \nu}(01)$ ist hierbei der kleinere Wert aus dem Vergleich von
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We assume the basic pulse values   $g_0\ne 0$,  $g_{\rm –1}\ne 0$  and  $g_{\rm –2}\ne 0$: 
:$${\it \Gamma}_{\nu-1}(00) + \varepsilon_{\nu}(001) \hspace{0.15cm}{\rm und}
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*This means that the decision on the symbol  $a_{\rm \nu}$  is also influenced by the subsequent coefficients  $a_{\rm \nu +1}$  and  $a_{\rm \nu +2}$. 
\hspace{0.15cm}{\it \Gamma}_{\nu-1}(10) + \varepsilon_{\nu}(101).$$
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 +
*Thus,  for each time point   $\nu$,  exactly eight  '''metrics'''   $\varepsilon_{\rm \nu}$  have to be determined, from which the  '''minimum accumulated metrics'''   ${\it \Gamma}_{\rm \nu}(00)$,  ${\it \Gamma}_{\rm \nu}(01)$,  ${\it \Gamma}_{\rm \nu}(10)$  and  ${\it \Gamma}_{\rm \nu}(11)$  can be calculated.
  
Zur Berechnung der minimalen Gesamtfehlergröße ${\it \Gamma}_2(10)$ in den Teilaufgaben (1) und (2) soll von folgenden Zahlenwerten ausgegangen werden:
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*For example,   ${\it \Gamma}_{\rm \nu}(01)$  provides information about the symbol  $a_{\rm \nu}$  under the assumption that  $a_{\rm \nu +1} = 0$  and  $a_{\rm \nu +2} = 1$  will be.
* unipolare Amplitudenkoeffizienten: $a_{\rm \nu} ∈ \{0, 1\}$,
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* Grundimpulswerte $g_0 = 0.5$, $g_{\rm –1} = 0.3$, $g_{\rm –2} = 0.2$,
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*Here, the minimum accumulated metric   ${\it \Gamma}_{\rm \nu}(01)$  is the smaller value obtained from the comparison of
* anliegender Detektionsabtastwert: $d_2 = 0.2$,  
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:$$\big[{\it \Gamma}_{\nu-1}(00) + \varepsilon_{\nu}(001)\big] \hspace{0.15cm}{\rm and}
* Minimale Gesamtfehlergrößen zum Zeitpunkt $\nu = 1$:
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\hspace{0.15cm}\big[{\it \Gamma}_{\nu-1}(10) + \varepsilon_{\nu}(101)\big].$$
:$${\it \Gamma}_{1}(00) = 0.0,\hspace{0.2cm}{\it \Gamma}_{1}(01) = 0.2, \hspace{1cm} {\it \Gamma}_{1}(10) = 0.6,\hspace{0.2cm}{\it \Gamma}_{1}(11) =
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 +
To calculate the minimum accumulated metric   ${\it \Gamma}_2(10)$  in subtasks '''(1)''' and '''(2)''',  assume the following numerical values:
 +
* unipolar amplitude coefficients:  $a_{\rm \nu} ∈ \{0, 1\}$,
 +
 
 +
* basic pulse values   $g_0 = 0.5$,  $g_{\rm –1} = 0.3$,  $g_{\rm –2} = 0.2$,
 +
 
 +
* applied noisy detection sample:  $d_2 = 0.2$,
 +
 +
* minimum accumulated metric at time  $\nu = 1$:
 +
:$${\it \Gamma}_{1}(00) = 0.0,\hspace{0.2cm}{\it \Gamma}_{1}(01) = 0.2, \hspace{0.2cm} {\it \Gamma}_{1}(10) = 0.6,\hspace{0.2cm}{\it \Gamma}_{1}(11) =
 
  1.2
 
  1.2
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
In der Grafik ist das vereinfachte Trellisdiagramm für die Zeitpunkte $\nu = 1$ bis $\nu = 8$ dargestellt. Blaue Zweige kommen entweder von ${\it \Gamma}_{\rm \nu –1}(00)$ oder von ${\it \Gamma}_{\rm \nu –1}(01)$ und kennzeichnen eine hypothetische „$0$”. Dagegen weisen alle roten Zweige – ausgehend von den Zuständen ${\it \Gamma}_{\rm \nu –1}(10)$ bzw. ${\it \Gamma}_{\rm \nu –1}(11)$ – jeweils auf das Symbol „$1$” hin
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The graph shows the simplified trellis diagram for time points   $\nu = 1$  to   $\nu = 8$. 
 +
*Blue branches come from either   ${\it \Gamma}_{\rm \nu –1}(00)$   or   ${\it \Gamma}_{\rm \nu –1}(01)$   and denote a hypothetical  "$0$".
 +
 +
*In contrast,  all red branches – starting from the   ${\it \Gamma}_{\rm \nu –1}(10)$  or   ${\it \Gamma}_{\rm \nu –1}(11)$  states – indicate the symbol  "$1$".
 +
 
 +
 
 +
 
 +
Notes:
 +
*The exercise belongs to the chapter   [[Digital_Signal_Transmission/Viterbi_Receiver|"Viterbi Receiver"]].
 +
 +
* All quantities here are to be understood normalized.
 +
 
 +
* Also, assume unipolar and equal probability amplitude coefficients:   ${\rm Pr} (a_\nu = 0) = {\rm Pr} (a_\nu = 1)= 0.5.$
  
''Hinweise:''
 
* Die Aufgabe gehört zum Themengebiet von Kapitel [[Digitalsignal%C3%BCbertragung/Viterbi%E2%80%93Empf%C3%A4nger| Viterbi–Empfänger]].
 
* Alle Größen sind hier normiert zu verstehen.
 
* Die hier angesprochene Thematik wird auch im folgenden Interaktionsmodul behandelt: [https://intern.lntwww.de/cgi-bin/extern/uni.pl?uno=hyperlink&due=block&b_id=2010&hyperlink_typ=block_verweis&hyperlink_fenstergroesse=blockverweis_gross| Eigenschaften des Viterbi–Empfängers].
 
  
  
===Fragebogen===
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===Questions===
 
<quiz display=simple>
 
<quiz display=simple>
{Berechnen Sie die folgenden Fehlergrößen:
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{Calculate the following metrics:
 
|type="{}"}
 
|type="{}"}
$\epsilon_2(010)$ = { 0.01 3% }
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$\varepsilon_2(010) \ = \ $ { 0.01 3% }
$\epsilon_2(011)$ = { 0.09 3% }
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$\varepsilon_2(011) \ = \ $ { 0.09 3% }
$\epsilon_2(110)$ = { 0.36 3% }
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$\varepsilon_2(110) \ = \ $ { 0.36 3% }
$\epsilon_2(111)$ = { 0.64 3% }
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$\varepsilon_2(111) \ = \ $ { 0.64 3% }
  
{Berechnen Sie die folgenden minimalen Gesamtfehlergrößen:
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{Calculate the following minimum accumulated metrics:
 
|type="{}"}
 
|type="{}"}
${\it \Gamma}_2(10)$ = { 0.21 3% }
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${\it \Gamma}_2(10) \ = \ $ { 0.21 3% }
${\it \Gamma}_2(11)$ = { 0.29 3% }
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${\it \Gamma}_2(11) \ = \ $ { 0.29 3% }
  
{Wie lauten die vom Viterbi&ndash;Empfänger ausgegebene Symbole?
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{What are the symbols output by the Viterbi receiver?
 
|type="[]"}
 
|type="[]"}
+ Die ersten sieben Symbole sind $1011010$.
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+ The first seven symbols are &nbsp; "$1011010$".
- Die ersten sieben Symbole sind $1101101$.
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- The first seven symbols are &nbsp; "$1101101$".
- Das letzte Symbol $a_8 = 1$ ist sicher.
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- The last symbol &nbsp;$a_8 = 1$&nbsp; is safe.
+ Über das Symbol $a_8$ ist noch keine endgültige Aussage möglich.
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+ No definite statement can be made about the symbol &nbsp;$a_8$.&nbsp;
 
</quiz>
 
</quiz>
  
===Musterlösung===
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===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''&nbsp; Die erste Fehlergröße wird wie folgt berechnet:
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'''(1)'''&nbsp; The first metric is calculated as follows:
 
:$$\varepsilon_{2}(010)  = [d_0 - 0 \cdot g_0 - 1 \cdot g_{-1}- 0 \cdot g_{-2}]^2= [0.2 -0.3]^2\hspace{0.15cm}\underline {=0.01}
 
:$$\varepsilon_{2}(010)  = [d_0 - 0 \cdot g_0 - 1 \cdot g_{-1}- 0 \cdot g_{-2}]^2= [0.2 -0.3]^2\hspace{0.15cm}\underline {=0.01}
 
   \hspace{0.05cm}.$$
 
   \hspace{0.05cm}.$$
  
Entsprechend gilt für die weiteren Fehlergrößen:
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Correspondingly,&nbsp; for the other metrics:
 
:$$\varepsilon_{2}(011) \ = \  [0.2 -0.3- 0.2]^2\hspace{0.15cm}\underline {=0.09}\hspace{0.05cm},$$
 
:$$\varepsilon_{2}(011) \ = \  [0.2 -0.3- 0.2]^2\hspace{0.15cm}\underline {=0.09}\hspace{0.05cm},$$
 
:$$\varepsilon_{2}(110) \ = \  [0.2 -0.5- 0.3]^2\hspace{0.15cm}\underline {=0.36}\hspace{0.05cm},$$
 
:$$\varepsilon_{2}(110) \ = \  [0.2 -0.5- 0.3]^2\hspace{0.15cm}\underline {=0.36}\hspace{0.05cm},$$
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'''(2)'''&nbsp; Die Aufgabe ist, jeweils den minimalen von zwei Vergleichswerten zu finden:
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'''(2)'''&nbsp; The task is to find the minimum value of each of two comparison values:
 
:$${\it \Gamma}_{2}(10) \ = \ {\rm Min}\left[{\it \Gamma}_{1}(01) + \varepsilon_{2}(010),
 
:$${\it \Gamma}_{2}(10) \ = \ {\rm Min}\left[{\it \Gamma}_{1}(01) + \varepsilon_{2}(010),
  \hspace{0.2cm}{\it \Gamma}_{1}(11) + \varepsilon_{2}(110)\right] = $$
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  \hspace{0.2cm}{\it \Gamma}_{1}(11) + \varepsilon_{2}(110)\right] = {\rm Min}\left[0.2+ 0.01, 1.2 + 0.36\right]\hspace{0.15cm}\underline {= 0.21}
:$$\ = \ {\rm Min}\left[0.2+ 0.01, 1.2 + 0.36\right]\hspace{0.15cm}\underline {= 0.21}
 
 
  \hspace{0.05cm},$$
 
  \hspace{0.05cm},$$
 
:$${\it \Gamma}_{2}(11) \ = \ {\rm Min}\left[{\it \Gamma}_{1}(01) + \varepsilon_{2}(011),
 
:$${\it \Gamma}_{2}(11) \ = \ {\rm Min}\left[{\it \Gamma}_{1}(01) + \varepsilon_{2}(011),
  \hspace{0.2cm}{\it \Gamma}_{1}(11) + \varepsilon_{2}(111)\right] = $$
+
  \hspace{0.2cm}{\it \Gamma}_{1}(11) + \varepsilon_{2}(111)\right] = {\rm Min}\left[0.2+ 0.09, 1.2 + 0.64\right]\hspace{0.15cm}\underline {= 0.29}
:$$\ = \ {\rm Min}\left[0.2+ 0.09, 1.2 + 0.64\right]\hspace{0.15cm}\underline {= 0.29}
 
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
  
'''(3)'''&nbsp; Richtig sind der <u>erste und der letzte Lösungsvorschlag</u>. Die Folge $1011010$ erkennt man aus dem durchgehenden Pfad:
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'''(3)'''&nbsp; The&nbsp; <u>first and last solutions</u>&nbsp; are correct:
# Rot &ndash; Blau &ndash; Rot &ndash; Rot &ndash; Blau &ndash; Rot &ndash; Blau.
+
*The sequence&nbsp; "$1011010$"&nbsp; can be recognized from the continuous path: &nbsp; &nbsp; "red &ndash; blue &ndash; red &ndash; red &ndash; blue &ndash; red &ndash; blue".
  
 +
*On the other hand,&nbsp; no final statement can be made about the symbol&nbsp; $a_8$&nbsp; at time&nbsp; $\nu = 8$:
  
Dagegen kann über das Symbol $a_8$ zum Zeitpunkt $\nu = 8$ noch keine endgültige Aussage gemacht werden: Nur unter der Hypothese $a_9 = 1$ and $a_{\rm 10} = 1$ würde man sich für $a_8 = 0$ entscheiden, bei anderen Hypothesen für $a_8 = 1$.
+
*Only under the hypothesis&nbsp; $a_9 = 1$&nbsp; <u>and</u>&nbsp; $a_{\rm 10} = 1$&nbsp; one would decide for&nbsp; $a_8 = 0$,&nbsp; under other hypotheses for&nbsp; $a_8 = 1$.
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  
  
  
[[Category:Aufgaben zu Digitalsignalübertragung|^3.8 Viterbi-Empfänger^]]
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[[Category:Digital Signal Transmission: Exercises|^3.8 Viterbi Receiver^]]

Latest revision as of 17:34, 4 July 2022

Trellis diagram for two precursors

We assume the basic pulse values   $g_0\ne 0$,  $g_{\rm –1}\ne 0$  and  $g_{\rm –2}\ne 0$: 

  • This means that the decision on the symbol  $a_{\rm \nu}$  is also influenced by the subsequent coefficients  $a_{\rm \nu +1}$  and  $a_{\rm \nu +2}$. 
  • Thus,  for each time point   $\nu$,  exactly eight  metrics   $\varepsilon_{\rm \nu}$  have to be determined, from which the  minimum accumulated metrics   ${\it \Gamma}_{\rm \nu}(00)$,  ${\it \Gamma}_{\rm \nu}(01)$,  ${\it \Gamma}_{\rm \nu}(10)$  and  ${\it \Gamma}_{\rm \nu}(11)$  can be calculated.
  • For example,   ${\it \Gamma}_{\rm \nu}(01)$  provides information about the symbol  $a_{\rm \nu}$  under the assumption that  $a_{\rm \nu +1} = 0$  and  $a_{\rm \nu +2} = 1$  will be.
  • Here, the minimum accumulated metric   ${\it \Gamma}_{\rm \nu}(01)$  is the smaller value obtained from the comparison of
$$\big[{\it \Gamma}_{\nu-1}(00) + \varepsilon_{\nu}(001)\big] \hspace{0.15cm}{\rm and} \hspace{0.15cm}\big[{\it \Gamma}_{\nu-1}(10) + \varepsilon_{\nu}(101)\big].$$

To calculate the minimum accumulated metric   ${\it \Gamma}_2(10)$  in subtasks (1) and (2),  assume the following numerical values:

  • unipolar amplitude coefficients:  $a_{\rm \nu} ∈ \{0, 1\}$,
  • basic pulse values   $g_0 = 0.5$,  $g_{\rm –1} = 0.3$,  $g_{\rm –2} = 0.2$,
  • applied noisy detection sample:  $d_2 = 0.2$,
  • minimum accumulated metric at time  $\nu = 1$:
$${\it \Gamma}_{1}(00) = 0.0,\hspace{0.2cm}{\it \Gamma}_{1}(01) = 0.2, \hspace{0.2cm} {\it \Gamma}_{1}(10) = 0.6,\hspace{0.2cm}{\it \Gamma}_{1}(11) = 1.2 \hspace{0.05cm}.$$

The graph shows the simplified trellis diagram for time points   $\nu = 1$  to   $\nu = 8$. 

  • Blue branches come from either   ${\it \Gamma}_{\rm \nu –1}(00)$   or   ${\it \Gamma}_{\rm \nu –1}(01)$   and denote a hypothetical  "$0$".
  • In contrast,  all red branches – starting from the   ${\it \Gamma}_{\rm \nu –1}(10)$  or   ${\it \Gamma}_{\rm \nu –1}(11)$  states – indicate the symbol  "$1$".


Notes:

  • All quantities here are to be understood normalized.
  • Also, assume unipolar and equal probability amplitude coefficients:   ${\rm Pr} (a_\nu = 0) = {\rm Pr} (a_\nu = 1)= 0.5.$


Questions

1

Calculate the following metrics:

$\varepsilon_2(010) \ = \ $

$\varepsilon_2(011) \ = \ $

$\varepsilon_2(110) \ = \ $

$\varepsilon_2(111) \ = \ $

2

Calculate the following minimum accumulated metrics:

${\it \Gamma}_2(10) \ = \ $

${\it \Gamma}_2(11) \ = \ $

3

What are the symbols output by the Viterbi receiver?

The first seven symbols are   "$1011010$".
The first seven symbols are   "$1101101$".
The last symbol  $a_8 = 1$  is safe.
No definite statement can be made about the symbol  $a_8$. 


Solution

(1)  The first metric is calculated as follows:

$$\varepsilon_{2}(010) = [d_0 - 0 \cdot g_0 - 1 \cdot g_{-1}- 0 \cdot g_{-2}]^2= [0.2 -0.3]^2\hspace{0.15cm}\underline {=0.01} \hspace{0.05cm}.$$

Correspondingly,  for the other metrics:

$$\varepsilon_{2}(011) \ = \ [0.2 -0.3- 0.2]^2\hspace{0.15cm}\underline {=0.09}\hspace{0.05cm},$$
$$\varepsilon_{2}(110) \ = \ [0.2 -0.5- 0.3]^2\hspace{0.15cm}\underline {=0.36}\hspace{0.05cm},$$
$$\varepsilon_{2}(111) \ = \ [0.2 -0.5- 0.3-0.2]^2\hspace{0.15cm}\underline {=0.64} \hspace{0.05cm}.$$


(2)  The task is to find the minimum value of each of two comparison values:

$${\it \Gamma}_{2}(10) \ = \ {\rm Min}\left[{\it \Gamma}_{1}(01) + \varepsilon_{2}(010), \hspace{0.2cm}{\it \Gamma}_{1}(11) + \varepsilon_{2}(110)\right] = {\rm Min}\left[0.2+ 0.01, 1.2 + 0.36\right]\hspace{0.15cm}\underline {= 0.21} \hspace{0.05cm},$$
$${\it \Gamma}_{2}(11) \ = \ {\rm Min}\left[{\it \Gamma}_{1}(01) + \varepsilon_{2}(011), \hspace{0.2cm}{\it \Gamma}_{1}(11) + \varepsilon_{2}(111)\right] = {\rm Min}\left[0.2+ 0.09, 1.2 + 0.64\right]\hspace{0.15cm}\underline {= 0.29} \hspace{0.05cm}.$$


(3)  The  first and last solutions  are correct:

  • The sequence  "$1011010$"  can be recognized from the continuous path:     "red – blue – red – red – blue – red – blue".
  • On the other hand,  no final statement can be made about the symbol  $a_8$  at time  $\nu = 8$:
  • Only under the hypothesis  $a_9 = 1$  and  $a_{\rm 10} = 1$  one would decide for  $a_8 = 0$,  under other hypotheses for  $a_8 = 1$.