Difference between revisions of "Aufgaben:Exercise 4.09: Decision Regions at Laplace"

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{{quiz-Header|Buchseite=Digitalsignalübertragung/Approximation der Fehlerwahrscheinlichkeit}}
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{{quiz-Header|Buchseite=Digital_Signal_Transmission/Approximation_of_the_Error_Probability}}
  
[[File:P_ID2044__Dig_A_4_9.png|right|frame|Drei verschiedene Entscheidungsregionen für Laplace]]
+
[[File:P_ID2044__Dig_A_4_9.png|right|frame|Three Laplace decision regions]]
Wir betrachten ein Übertragungssystem, basierend auf den Basisfunktionen $\varphi_1(t)$ und $\varphi_2(t)$. Die zwei gleichwahrscheinlichen Sendesignale sind durch die Signalpunkte
+
We consider a transmission system based on the basis functions  $\varphi_1(t)$  and  $\varphi_2(t)$.  The two equally probable transmitted signals are given by the signal points
 
:$$\boldsymbol{ s }_0 = (-\sqrt{E}, \hspace{0.1cm}-\sqrt{E})\hspace{0.05cm}, \hspace{0.2cm}  
 
:$$\boldsymbol{ s }_0 = (-\sqrt{E}, \hspace{0.1cm}-\sqrt{E})\hspace{0.05cm}, \hspace{0.2cm}  
   \boldsymbol{ s }_1 = (+\sqrt{E}, \hspace{0.1cm}+\sqrt{E})\hspace{0.05cm}$$
+
   \boldsymbol{ s }_1 = (+\sqrt{E}, \hspace{0.1cm}+\sqrt{E})\hspace{0.05cm}.$$
  
gegeben. Im Folgenden normieren wir zur Vereinfachung den Energieparameter zu $E = 1$ und erhalten somit
+
In the following we normalize the energy parameter to  $E = 1$  for simplification and thus obtain
:$$\boldsymbol{ s }_0 \hspace{-0.1cm} \ = \ \hspace{-0.1cm} (-1, \hspace{0.1cm}-1) \hspace{0.2cm} \Longleftrightarrow \hspace{0.2cm} m_0\hspace{0.05cm}, $$
+
:$$\boldsymbol{ s }_0 \hspace{-0.1cm} \ = \ \hspace{-0.1cm} (-1, \hspace{0.1cm}-1) \hspace{0.2cm} \Leftrightarrow \hspace{0.2cm} m_0\hspace{0.05cm}, $$
:$$  \boldsymbol{ s }_1 \hspace{-0.1cm} \ = \ \hspace{-0.1cm}  (+1, \hspace{0.1cm}+1)\hspace{0.2cm} \Longleftrightarrow \hspace{0.2cm} m_1\hspace{0.05cm}.$$
+
:$$  \boldsymbol{ s }_1 \hspace{-0.1cm} \ = \ \hspace{-0.1cm}  (+1, \hspace{0.1cm}+1)\hspace{0.2cm} \Leftrightarrow \hspace{0.2cm} m_1\hspace{0.05cm}.$$
  
Die Nachrichten $m_0$ und $m_1$ sind den so festgelegten Signalen $\boldsymbol{s}_0$ und $\boldsymbol{s}_1$ eindeutig zugeordnet.
+
The messages  $m_0$  and  $m_1$  are uniquely assigned to the signals  $\boldsymbol{s}_0$  and  $\boldsymbol{s}_1$  defined in this way.
  
Die zwei Rauschkomponenten $n_1(t)$ und $n_2(t)$ seien unabhängig voneinander und jeweils laplace–verteilt mit Parameter $a = 1$:
+
Let the noise components  $n_1(t)$  and  $n_2(t)$  be independent of each other and each be Laplace distributed with parameter  $a = 1$:
 
:$$p_{n_1} (\eta_1) =  {1}/{2} \cdot  {\rm e}^{- | \eta_1|} \hspace{0.05cm}, \hspace{0.2cm}
 
:$$p_{n_1} (\eta_1) =  {1}/{2} \cdot  {\rm e}^{- | \eta_1|} \hspace{0.05cm}, \hspace{0.2cm}
  p_{n_2} (\eta_2) = {1}/{2} \cdot  {\rm e}^{- | \eta_2|} \hspace{0.05cm}$$
+
  p_{n_2} (\eta_2) = {1}/{2} \cdot  {\rm e}^{- | \eta_2|} \hspace{0.05cm} \hspace{0.3cm}
:$$\Rightarrow \hspace{0.3cm} \boldsymbol{ p }_{\boldsymbol{ n }} (\eta_1, \eta_2) =  {1}/{4} \cdot  {\rm e}^{- | \eta_1|- | \eta_2|} \hspace{0.05cm}. $$
+
\Rightarrow \hspace{0.3cm} \boldsymbol{ p }_{\boldsymbol{ n }} (\eta_1, \eta_2) =  {1}/{4} \cdot  {\rm e}^{- | \eta_1|- | \eta_2|} \hspace{0.05cm}. $$
  
Die Eigenschaften eines solchen Laplace–Rauschens werden in der [[Zusatzaufgaben:4.9_Laplace-verteiltes_Rauschen| Aufgabe Z4.9]] noch eingehend behandelt.
+
The properties of such a Laplace noise will be discussed in detail in  [[Aufgaben:Exercise_4.09Z:_Laplace_Distributed_Noise|"Exercise 4.9Z"]]. 
  
Das Empfangssignal $\boldsymbol{r}$ setzt sich additiv aus dem Sendesignal $\boldsymbol{s}$ und dem Rauschsignal $\boldsymbol{n}$ zusammen:
+
The received signal  $\boldsymbol{r}$  is composed additively of the transmitted signal  $\boldsymbol{s}$  and the  noise component  $\boldsymbol{n}$:
 
:$$\boldsymbol{ r } \hspace{-0.1cm} \ = \ \hspace{-0.1cm} \boldsymbol{ s } + \boldsymbol{ n }
 
:$$\boldsymbol{ r } \hspace{-0.1cm} \ = \ \hspace{-0.1cm} \boldsymbol{ s } + \boldsymbol{ n }
 
   \hspace{0.05cm}, \hspace{0.45cm}\boldsymbol{ r } = ( r_1, r_2)
 
   \hspace{0.05cm}, \hspace{0.45cm}\boldsymbol{ r } = ( r_1, r_2)
   \hspace{0.05cm},$$
+
   \hspace{0.05cm},\hspace{0.45cm}
:$$ \boldsymbol{ s } \hspace{-0.1cm} \ = \ \hspace{-0.1cm} ( s_1, s_2)
+
\boldsymbol{ s } \hspace{-0.1cm} \ = \ \hspace{-0.1cm} ( s_1, s_2)
   \hspace{0.05cm}, \hspace{0.2cm}\boldsymbol{ n } = ( n_1, n_2)  
+
   \hspace{0.05cm}, \hspace{0.8cm}\boldsymbol{ n } = ( n_1, n_2)  
 
   \hspace{0.05cm}. $$
 
   \hspace{0.05cm}. $$
  
Die entsprechend Realisierungen sind wie folgt bezeichnet:
+
The corresponding realizations are denoted as follows:
:$$\boldsymbol{ s }\hspace{-0.1cm} \ : \ \hspace{-0.1cm} \hspace{0.1cm} (s_{01},s_{02}){\hspace{0.15cm}\rm bzw. \hspace{0.15cm}} (s_{11},s_{12})  
+
:$$\boldsymbol{ s }\text{:} \hspace{0.4cm} (s_{01},s_{02}){\hspace{0.15cm}\rm and \hspace{0.15cm}} (s_{11},s_{12})  
   \hspace{0.05cm},$$
+
   \hspace{0.05cm},\hspace{0.8cm} \boldsymbol{ r }\text{:} \hspace{0.4cm} (\rho_{1},\rho_{2})
:$$ \boldsymbol{ r } \hspace{-0.1cm} \ : \ \hspace{-0.1cm} \hspace{0.1cm} (\rho_{1},\rho_{2})
+
   \hspace{0.05cm}, \hspace{0.8cm}\boldsymbol{ n }\text{:} \hspace{0.4cm} (\eta_{1},\eta_{2})
   \hspace{0.05cm}, \hspace{0.2cm}\boldsymbol{ n }: \hspace{0.1cm} (\eta_{1},\eta_{2})
 
 
   \hspace{0.05cm}.$$
 
   \hspace{0.05cm}.$$
  
Die Entscheidungsregel des MAP– und des ML–Empfängers (beide sind aufgrund der gleichen Symbolwahrscheinlichkeiten identisch) lauten:
+
The decision rule of the MAP and ML receivers  $($both are identical due to the same symbol probabilities$)$  are:
  
Entscheide für das Symbol $m_0$, falls
+
⇒   Decide for the symbol  $m_0$, if   $p_{\boldsymbol{ r} \hspace{0.05cm}|\hspace{0.05cm}m } ( \rho_{1},\rho_{2} |m_0 ) >  
:$$p_{\boldsymbol{ r} \hspace{0.05cm}|\hspace{0.05cm}m } ( \rho_{1},\rho_{2} |m_0 ) >  
+
p_{\boldsymbol{ r} \hspace{0.05cm}|\hspace{0.05cm}m } (\rho_{1},\rho_{2} |m_1 ) \hspace{0.05cm}.$
p_{\boldsymbol{ r} \hspace{0.05cm}|\hspace{0.05cm}m } (\rho_{1},\rho_{2} |m_1 ) \hspace{0.05cm}.$$
 
  
Mit den weiteren Voraussetzungen kann hierfür (Entscheidung für $m_0$) auch geschrieben werden:
+
⇒   With the further conditions for the  "decision for  $m_0$"  can also be written:
 
:$${1}/{4} \cdot  {\rm exp}\left [- | \rho_1 +1|- | \rho_2 +1| \hspace{0.1cm} \right ] >
 
:$${1}/{4} \cdot  {\rm exp}\left [- | \rho_1 +1|- | \rho_2 +1| \hspace{0.1cm} \right ] >
 
   {1}/{4} \cdot  {\rm exp}\left [- | \rho_1 -1|- | \rho_2 -1| \hspace{0.1cm} \right ] $$
 
   {1}/{4} \cdot  {\rm exp}\left [- | \rho_1 -1|- | \rho_2 -1| \hspace{0.1cm} \right ] $$
Line 49: Line 47:
 
   | \rho_1 -1|- | \rho_2 -1| < 0 \hspace{0.05cm}.$$
 
   | \rho_1 -1|- | \rho_2 -1| < 0 \hspace{0.05cm}.$$
  
Auf diese Funktion $L(\rho_1, \rho_2)$ wird in den nachfolgenden Aufgaben häufig Bezug genommen.
+
&rArr; &nbsp; This function&nbsp; $L(\rho_1, \rho_2)$&nbsp; is frequently referred to in the questions.
 +
 
 +
 
 +
The graph shows three different decision regions&nbsp; $(I_0, \ I_1)$.
 +
:*For AWGN noise,&nbsp; only the upper variant &nbsp;$\rm A$&nbsp; would be optimal.
 +
 
 +
:*Also for the considered Laplace noise, variant &nbsp;$\rm A$&nbsp; leads to the smallest possible error probability, see&nbsp; [[Aufgaben:Exercise_4.09Z:_Laplace_Distributed_Noise|"Exercise 4.9Z"]]:
 +
::$$p_{\rm min} = {\rm Pr}({\cal{E}} \hspace{0.05cm}|\hspace{0.05cm} {\rm optimal\hspace{0.15cm} receiver}) = {\rm e}^{-2} \approx 13.5\,\%\hspace{0.05cm}.$$
 +
:*It is to be examined whether variant &nbsp;$\rm B$&nbsp; or variant &nbsp;$\rm C$&nbsp; is also optimal, i.e. whether their error probabilities are also as small as possible equal to &nbsp;$p_{\rm min}$.&nbsp;
 +
 
  
Die Grafik zeigt drei verschiedene Entscheidungsregionen ($I_0, I_1$). Bei AWGN&ndash;Rauschen wäre nur die obere Variante <i>A</i> optimal. Auch beim hier betrachteten Laplace&ndash;Rauschen führt die Variante <i>A</i> zur kleinstmöglichen Fehlerwahrscheinlichkeit, siehe [[Zusatzaufgaben:4.9_Laplace-verteiltes_Rauschen| Aufgabe Z4.9]]:
 
:$$p_{\rm min} = {\rm Pr}({\cal{E}} \hspace{0.05cm}|\hspace{0.05cm} {\rm optimaler\hspace{0.15cm} Empf\ddot{a}nger}) = {\rm e}^{-2} \approx 13.5\,\%\hspace{0.05cm}.$$
 
  
Zu untersuchen ist, ob die Variante <i>B</i> bzw. die Variante <i>C</i> ebenfalls optimal ist, das heißt, ob auch deren Fehlerwahrscheinlichkeiten kleinstmöglich gleich $\rho_{\rm min}$ sind.
+
Note: &nbsp;  The exercise belongs to the chapter&nbsp; [[Digital_Signal_Transmission/Approximation_of_the_Error_Probability|"Approximation of the Error Probability"]].  
 +
  
''Hinweis:''
 
* Die Aufgabe bezieht sich auf die letzten Theorieseiten des Kapitels [[Digitalsignal%C3%BCbertragung/Approximation_der_Fehlerwahrscheinlichkeit| Approximation der Fehlerwahrscheinlichkeit]].
 
  
  
  
===Fragebogen===
+
===Questions===
 
<quiz display=simple>
 
<quiz display=simple>
{Multiple-Choice
+
{Which of the decision rules are correct?&nbsp; Decide for&nbsp; $m_0$,&nbsp; if
 +
|type="[]"}
 +
+ $p_{\it r\hspace{0.03cm}|\hspace{0.03cm}m}(\rho_1, \ \rho_2\hspace{0.03cm}|\hspace{0.03cm}m_0) > p_{\it r\hspace{0.03cm}|\hspace{0.03cm}m}(\rho_1, \ \rho_2\hspace{0.03cm}|\hspace{0.03cm}m_1)$,
 +
+ $L(\rho_1, \ \rho_2) = |\rho_1+1| \, -|\rho_1 \, &ndash;1| + |\rho_2+1| \, -|\rho_2 \, &ndash;1| < 0$,
 +
- $L(\rho_1, \ \rho_2) = \rho_1 + \rho_2 &#8805; 0$.
 +
 
 +
{How can the expression&nbsp; $|x+1| \ -|x \ -1|$&nbsp; be transformed?
 
|type="[]"}
 
|type="[]"}
+ correct
+
+ For&nbsp; $x &#8805; +1$:&nbsp; &nbsp; $|x + 1| \, -|x -1| = 2$.
- false
+
+ For&nbsp; $x &#8804; \, -1$:&nbsp; &nbsp; $|x+1| \,-|x \, -1| = \, -2$.
 +
+ For&nbsp; $-1 &#8804; x &#8804; +1$:&nbsp; &nbsp; $|x+1| \, -|x \, -1| = 2x$.
 +
 
 +
{What is the decision rule in the range&nbsp; $-1 &#8804; \rho_1 &#8804; +1$,&nbsp; $-1 &#8804; \rho_2 &#8804; +1$?
 +
|type="()"}
 +
+ Decision for&nbsp; $m_0$,&nbsp; if&nbsp; $\rho_1 + \rho_2 < 0$.
 +
- Decision for&nbsp; $m_1$,&nbsp; if&nbsp; $\rho_1 + \rho_2 < 0$.
 +
 
 +
{What is the decision rule in the range&nbsp; $\rho_1 > +1$?
 +
|type="()"}
 +
- Decision for&nbsp; $m_0$&nbsp; in the whole range.
 +
+ Decision for&nbsp; $m_1$&nbsp; in the whole range.
 +
- Decision for&nbsp; $m_0$&nbsp; only if&nbsp; $\rho_1 + \rho_2 < 0$.
 +
 
 +
{What is the decision rule in the range&nbsp; $\rho_1 < \, -1$?
 +
|type="()"}
 +
+ Decision for&nbsp; $m_0$&nbsp; in the whole range.
 +
- Decision for&nbsp; $m_1$&nbsp; in the whole range.
 +
- Decision for&nbsp; $m_0$&nbsp; only if&nbsp; $\rho_1 + \rho_2 < 0$.
 +
 
 +
{What is the decision rule in the range&nbsp; $\rho_2 > +1$?
 +
|type="()"}
 +
- Decision for&nbsp; $m_0$&nbsp; in the whole range.
 +
+ Decision for&nbsp; $m_1$&nbsp; in the whole range.
 +
- Decision for&nbsp; $m_0$&nbsp; only if&nbsp; $\rho_1 + \rho_2 < 0$.
  
{Input-Box Frage
+
{What is the decision rule in the range&nbsp; $\rho_2 <  -1$?
|type="{}"}
+
|type="()"}
$xyz$ = { 5.4 3% } $ab$
+
+ Decision for&nbsp; $m_0$&nbsp; in the whole range.
 +
- Decision for&nbsp; $m_1$&nbsp; in the whole range.
 +
- Decision for&nbsp; $m_0$&nbsp; only if&nbsp; $\rho_1 + \rho_2 < 0$.
 +
 
 +
{Which of the following statements are true?
 +
|type="[]"}
 +
+ Variant &nbsp;$\rm A$&nbsp; leads to the minimum error probability.
 +
+ Variant &nbsp;$\rm B$&nbsp; leads to the minimum error probability.
 +
- Variant &nbsp;$\rm C$&nbsp; leads to the minimum error probability.
 
</quiz>
 
</quiz>
  
===Musterlösung===
+
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''&nbsp;  
+
'''(1)'''&nbsp; <u>Solutions 1 and 2</u>&nbsp; are correct:
'''(2)'''&nbsp;  
+
*The joint probability densities under conditions&nbsp; $m_0$&nbsp; and&nbsp; $m_1$,&nbsp; respectively,&nbsp; are:
'''(3)'''&nbsp;  
+
:$$p_{\boldsymbol{ r} \hspace{0.05cm}|\hspace{0.05cm}m } ( \rho_{1},\rho_{2} |m_0 )
'''(4)'''&nbsp;  
+
\hspace{-0.1cm} \ = \ \hspace{-0.1cm} {1}/{4} \cdot  {\rm exp}\left [- | \rho_1 +1|- | \rho_2 +1| \hspace{0.05cm} \right ]\hspace{0.05cm},$$
'''(5)'''&nbsp;  
+
:$$p_{\boldsymbol{ r} \hspace{0.05cm}|\hspace{0.05cm}m } ( \rho_{1},\rho_{2} |m_1 )
 +
\hspace{-0.1cm} \ = \ \hspace{-0.1cm} {1}/{4} \cdot  {\rm exp}\left [- | \rho_1 -1|- | \rho_2 -1| \hspace{0.05cm} \right ]\hspace{0.05cm}.$$
 +
*For equally probable symbols &nbsp; &#8658; &nbsp; ${\rm Pr}(m_0) = {\rm Pr}(m_1) = 0.5$,&nbsp; the MAP decision rule is: &nbsp; Decide for symbol&nbsp; $m_0$&nbsp; &nbsp; &#8660; &nbsp; signal&nbsp; $s_0$,&nbsp; if
 +
:$$p_{\boldsymbol{ r} \hspace{0.05cm}|\hspace{0.05cm}m } ( \rho_{1},\rho_{2} |m_0 ) >
 +
p_{\boldsymbol{ r} \hspace{0.05cm}|\hspace{0.05cm}m } (\rho_{1},\rho_{2} |m_1 ) \hspace{0.05cm}\hspace{0.3cm}
 +
\Rightarrow \hspace{0.3cm}  {1}/{4} \cdot  {\rm exp}\left [- | \rho_1 +1|- | \rho_2 +1| \hspace{0.05cm} \right ] >
 +
  {1}/{4} \cdot  {\rm exp}\left [- | \rho_1 -1|- | \rho_2 -1|\hspace{0.05cm} \right ] $$
 +
:$$\Rightarrow \hspace{0.3cm}  | \rho_1 +1|+ | \rho_2 +1| <
 +
  | \rho_1 -1|+ | \rho_2 -1|\hspace{0.3cm}
 +
\Rightarrow \hspace{0.3cm}  L (\rho_1, \rho_2) = | \rho_1 +1|-
 +
  | \rho_1 -1|+ | \rho_2 +1| - | \rho_2 -1| < 0 \hspace{0.05cm}.$$
 +
 
 +
 
 +
'''(2)'''&nbsp; <u>All statements are true</u>:
 +
*For $x &#8805; 1$:
 +
:$$| x +1|- | x -1| = x +1 -x +1 =2 \hspace{0.05cm}.$$
 +
 
 +
*Similarly,&nbsp; for $x &#8804; \, &ndash;1$,&nbsp; e.g.&nbsp; $x = \, &ndash;3$:
 +
:$$| x +1|- | x -1| = | -3 +1|- | -3 -1| = 2-4 = -2 \hspace{0.05cm}.$$
 +
 
 +
*On the other hand,&nbsp; in the middle range $&ndash;1 &#8804; x &#8804; +1$:
 +
:$$| x+1|- | x -1| = x +1 -1 +x =2x \hspace{0.05cm}.$$
 +
 
 +
 
 +
'''(3)'''&nbsp; <u>Solution 1</u>&nbsp; is correct:
 +
*The result of subtask&nbsp; '''(1)'''&nbsp; was:&nbsp; Decide for the symbol&nbsp; $m_0$,&nbsp; if
 +
:$$L (\rho_1, \rho_2) = | \rho_1 +1| -
 +
  | \rho_1 -1|+ | \rho_2 +1| - | \rho_2 -1| < 0 \hspace{0.05cm}.$$
 +
*In the considered&nbsp; (inner)&nbsp; range&nbsp; $-1 &#8804; \rho_1 &#8804; +1$,&nbsp; $-1 &#8804; \rho_2 &#8804; +1$&nbsp; holds with the result of subtask&nbsp; '''(2)''':
 +
:$$| \rho_1+1| - | \rho_1 -1| = 2\rho_1 \hspace{0.05cm}, \hspace{0.2cm} | \rho_2+1| - | \rho_2 -1| = 2\rho_2 \hspace{0.05cm}.$$
 +
 
 +
*If we insert this result above,&nbsp; we have to decide for&nbsp; $m_0$&nbsp; exactly if
 +
:$$L (\rho_1, \rho_2) = 2 \cdot ( \rho_1+\rho_2) < 0 
 +
\hspace{0.3cm} \Rightarrow \hspace{0.3cm} \rho_1+\rho_2 < 0\hspace{0.05cm}.$$
 +
 
 +
 
 +
'''(4)'''&nbsp; Correct is here&nbsp; <u>solution 2</u>:
 +
*For&nbsp; $\rho_1 > 1$ &nbsp; &rArr; &nbsp;  $|\rho_1+1| \, -|\rho_1 \, -1| = 2$,&nbsp; while for&nbsp; $D_2 = |\rho_2+1| \,-|\rho_2 \, -1|$ &nbsp; &rArr; &nbsp;  all values between&nbsp; $-2$&nbsp; and&nbsp; $+2$&nbsp; are possible.
 +
 
 +
*Thus,&nbsp; the decision variable is&nbsp; $L(\rho_1, \rho_2) = 2 + D_2 &#8805; 0$.&nbsp; In this case,&nbsp; the rule leads to an&nbsp; $m_1$&nbsp; decision.
 +
 
 +
 
 +
 
 +
'''(5)'''&nbsp; <u>Solution 1</u>&nbsp; is correct: 
 +
*After similar calculation as in subtask&nbsp; '''(3)''',&nbsp; one arrives at the result:
 +
:$$L (\rho_1, \rho_2) = -2 + D_2 \le 0  \hspace{0.3cm} \Rightarrow \hspace{0.3cm}
 +
  {\rm decision\hspace{0.15cm} on\hspace{0.15cm}} m_0\hspace{0.05cm}.$$
 +
 
 +
 
 +
'''(6)'''&nbsp; <u>Solution 2</u>&nbsp; is correct:&nbsp; Decision on&nbsp; $m_1$.
 +
*Similar to subtask&nbsp; '''(4)''',&nbsp; the following holds here:
 +
:$$D_1 = | \rho_1 +1| -    | \rho_1 -1| \in \{-2, ... \hspace{0.05cm} , +2 \}
 +
  \hspace{0.3cm} \Rightarrow \hspace{0.3cm}L (\rho_1, \rho_2) = 2 + D_1 \ge 0
 +
  \hspace{0.05cm}.$$
 +
 
 +
 
 +
'''(7)'''&nbsp; <u>Solution 1</u>&nbsp; is correct:&nbsp; Decision on&nbsp; $m_0$.
 +
*After similar reasoning as in the last subtask,&nbsp; we arrive at the result:
 +
:$$L (\rho_1, \rho_2) = -2 + D_1 \le 0  \hspace{0.3cm} \Rightarrow \hspace{0.3cm}
 +
  {\rm decision\hspace{0.15cm} on\hspace{0.15cm}} m_0\hspace{0.05cm}.$$
 +
 
 +
 
 +
[[File:P_ID2050__Dig_A_4_9h.png|right|frame|Summary of the results]]
 +
'''(8)'''&nbsp; The results of subtasks&nbsp; '''(3)'''&nbsp; to&nbsp; '''(7)'''&nbsp; are summarized in the graph:
 +
 
 +
* Subarea&nbsp; $T_0$: &nbsp;  Decision on&nbsp; $m_0$&nbsp; or&nbsp; $m_1$&nbsp; according to task&nbsp; '''(3)'''.
 +
* Subarea&nbsp; $T_1$: &nbsp;  Decision on&nbsp; $m_1$&nbsp; according to task&nbsp; '''(4)'''.
 +
* Subarea&nbsp; $T_2$: &nbsp;  Decision on&nbsp; $m_0$&nbsp; according to task&nbsp; '''(5)'''.
 +
* Subarea&nbsp; $T_3$: &nbsp;  Decision on&nbsp; $m_1$&nbsp; according to task&nbsp; '''(6)'''.
 +
* Subarea&nbsp; $T_4$: &nbsp; Decision on $m_0$&nbsp; according to task&nbsp; '''(7)'''.
 +
* Subarea&nbsp; $T_5$: &nbsp;  Decision on&nbsp; $m_0$&nbsp; according to task&nbsp; '''(5)''', and on&nbsp; $m_1$&nbsp; according to task&nbsp; '''(6)''' <br>&rArr; &nbsp; For Laplace noise,&nbsp; it does not matter whether one assigns&nbsp; $T_5$&nbsp; to region&nbsp; $I_0$&nbsp; or&nbsp; $I_1$.
 +
* Subarea&nbsp; $T_6$: &nbsp; Again,&nbsp; based on the results of task&nbsp; '''(6)'''&nbsp; and&nbsp; '''(7)''',&nbsp; one can assign this region to  region&nbsp; $I_0$&nbsp; or region&nbsp; $I_1$.
 +
 
 +
 
 +
It can be seen:
 +
#For subarea&nbsp; $T_0$,&nbsp;  ... ,&nbsp; $T_4$&nbsp; there is a fixed assignment to the decision regions&nbsp; $I_0$&nbsp; (red)&nbsp; and&nbsp; $I_1$&nbsp; (blue).
 +
#In contrast,&nbsp; the two yellow regions&nbsp; $T_5$&nbsp; and&nbsp; $T_6$&nbsp; can be assigned to both,&nbsp; $I_0$&nbsp; and&nbsp; $I_1$&nbsp; without loss of optimality.
 +
 
 +
 
 +
Comparing this graph with variants&nbsp; $\rm A$,&nbsp; $\rm B$&nbsp; and&nbsp; $\rm C$&nbsp; on the specification page,&nbsp; we see that&nbsp; <u>suggestions 1 and 2</u>&nbsp; are correct:
 +
# Variants&nbsp; $\rm A$&nbsp; and&nbsp; $\rm B$&nbsp;are equally good.&nbsp; Both are optimal.&nbsp; The error probability in both cases is&nbsp; $p_{\rm min} = {\rm e}^{\rm -2}$.
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# Variant&nbsp; $\rm C$&nbsp; is not optimal;&nbsp; with respect to the subareas&nbsp; $T_1$&nbsp; and&nbsp; $T_2$&nbsp; there are mismatches.&nbsp; The error probability is therefore greater than&nbsp; $p_{\rm min}$.
 
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[[Category:Aufgaben zu Digitalsignalübertragung|^4.3 BER-Approximation^]]
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[[Category:Digital Signal Transmission: Exercises|^4.3 BER Approximation^]]

Latest revision as of 16:49, 29 July 2022

Three Laplace decision regions

We consider a transmission system based on the basis functions  $\varphi_1(t)$  and  $\varphi_2(t)$.  The two equally probable transmitted signals are given by the signal points

$$\boldsymbol{ s }_0 = (-\sqrt{E}, \hspace{0.1cm}-\sqrt{E})\hspace{0.05cm}, \hspace{0.2cm} \boldsymbol{ s }_1 = (+\sqrt{E}, \hspace{0.1cm}+\sqrt{E})\hspace{0.05cm}.$$

In the following we normalize the energy parameter to  $E = 1$  for simplification and thus obtain

$$\boldsymbol{ s }_0 \hspace{-0.1cm} \ = \ \hspace{-0.1cm} (-1, \hspace{0.1cm}-1) \hspace{0.2cm} \Leftrightarrow \hspace{0.2cm} m_0\hspace{0.05cm}, $$
$$ \boldsymbol{ s }_1 \hspace{-0.1cm} \ = \ \hspace{-0.1cm} (+1, \hspace{0.1cm}+1)\hspace{0.2cm} \Leftrightarrow \hspace{0.2cm} m_1\hspace{0.05cm}.$$

The messages  $m_0$  and  $m_1$  are uniquely assigned to the signals  $\boldsymbol{s}_0$  and  $\boldsymbol{s}_1$  defined in this way.

Let the noise components  $n_1(t)$  and  $n_2(t)$  be independent of each other and each be Laplace distributed with parameter  $a = 1$:

$$p_{n_1} (\eta_1) = {1}/{2} \cdot {\rm e}^{- | \eta_1|} \hspace{0.05cm}, \hspace{0.2cm} p_{n_2} (\eta_2) = {1}/{2} \cdot {\rm e}^{- | \eta_2|} \hspace{0.05cm} \hspace{0.3cm} \Rightarrow \hspace{0.3cm} \boldsymbol{ p }_{\boldsymbol{ n }} (\eta_1, \eta_2) = {1}/{4} \cdot {\rm e}^{- | \eta_1|- | \eta_2|} \hspace{0.05cm}. $$

The properties of such a Laplace noise will be discussed in detail in  "Exercise 4.9Z"

The received signal  $\boldsymbol{r}$  is composed additively of the transmitted signal  $\boldsymbol{s}$  and the  noise component  $\boldsymbol{n}$:

$$\boldsymbol{ r } \hspace{-0.1cm} \ = \ \hspace{-0.1cm} \boldsymbol{ s } + \boldsymbol{ n } \hspace{0.05cm}, \hspace{0.45cm}\boldsymbol{ r } = ( r_1, r_2) \hspace{0.05cm},\hspace{0.45cm} \boldsymbol{ s } \hspace{-0.1cm} \ = \ \hspace{-0.1cm} ( s_1, s_2) \hspace{0.05cm}, \hspace{0.8cm}\boldsymbol{ n } = ( n_1, n_2) \hspace{0.05cm}. $$

The corresponding realizations are denoted as follows:

$$\boldsymbol{ s }\text{:} \hspace{0.4cm} (s_{01},s_{02}){\hspace{0.15cm}\rm and \hspace{0.15cm}} (s_{11},s_{12}) \hspace{0.05cm},\hspace{0.8cm} \boldsymbol{ r }\text{:} \hspace{0.4cm} (\rho_{1},\rho_{2}) \hspace{0.05cm}, \hspace{0.8cm}\boldsymbol{ n }\text{:} \hspace{0.4cm} (\eta_{1},\eta_{2}) \hspace{0.05cm}.$$

The decision rule of the MAP and ML receivers  $($both are identical due to the same symbol probabilities$)$  are:

⇒   Decide for the symbol  $m_0$, if   $p_{\boldsymbol{ r} \hspace{0.05cm}|\hspace{0.05cm}m } ( \rho_{1},\rho_{2} |m_0 ) > p_{\boldsymbol{ r} \hspace{0.05cm}|\hspace{0.05cm}m } (\rho_{1},\rho_{2} |m_1 ) \hspace{0.05cm}.$

⇒   With the further conditions for the  "decision for  $m_0$"  can also be written:

$${1}/{4} \cdot {\rm exp}\left [- | \rho_1 +1|- | \rho_2 +1| \hspace{0.1cm} \right ] > {1}/{4} \cdot {\rm exp}\left [- | \rho_1 -1|- | \rho_2 -1| \hspace{0.1cm} \right ] $$
$$\Rightarrow \hspace{0.3cm} | \rho_1 +1|+ | \rho_2 +1| < | \rho_1 -1|+ | \rho_2 -1|$$
$$\Rightarrow \hspace{0.3cm} L (\rho_1, \rho_2) = | \rho_1 +1|+ | \rho_2 +1| - | \rho_1 -1|- | \rho_2 -1| < 0 \hspace{0.05cm}.$$

⇒   This function  $L(\rho_1, \rho_2)$  is frequently referred to in the questions.


The graph shows three different decision regions  $(I_0, \ I_1)$.

  • For AWGN noise,  only the upper variant  $\rm A$  would be optimal.
  • Also for the considered Laplace noise, variant  $\rm A$  leads to the smallest possible error probability, see  "Exercise 4.9Z":
$$p_{\rm min} = {\rm Pr}({\cal{E}} \hspace{0.05cm}|\hspace{0.05cm} {\rm optimal\hspace{0.15cm} receiver}) = {\rm e}^{-2} \approx 13.5\,\%\hspace{0.05cm}.$$
  • It is to be examined whether variant  $\rm B$  or variant  $\rm C$  is also optimal, i.e. whether their error probabilities are also as small as possible equal to  $p_{\rm min}$. 


Note:   The exercise belongs to the chapter  "Approximation of the Error Probability".



Questions

1

Which of the decision rules are correct?  Decide for  $m_0$,  if

$p_{\it r\hspace{0.03cm}|\hspace{0.03cm}m}(\rho_1, \ \rho_2\hspace{0.03cm}|\hspace{0.03cm}m_0) > p_{\it r\hspace{0.03cm}|\hspace{0.03cm}m}(\rho_1, \ \rho_2\hspace{0.03cm}|\hspace{0.03cm}m_1)$,
$L(\rho_1, \ \rho_2) = |\rho_1+1| \, -|\rho_1 \, –1| + |\rho_2+1| \, -|\rho_2 \, –1| < 0$,
$L(\rho_1, \ \rho_2) = \rho_1 + \rho_2 ≥ 0$.

2

How can the expression  $|x+1| \ -|x \ -1|$  be transformed?

For  $x ≥ +1$:    $|x + 1| \, -|x -1| = 2$.
For  $x ≤ \, -1$:    $|x+1| \,-|x \, -1| = \, -2$.
For  $-1 ≤ x ≤ +1$:    $|x+1| \, -|x \, -1| = 2x$.

3

What is the decision rule in the range  $-1 ≤ \rho_1 ≤ +1$,  $-1 ≤ \rho_2 ≤ +1$?

Decision for  $m_0$,  if  $\rho_1 + \rho_2 < 0$.
Decision for  $m_1$,  if  $\rho_1 + \rho_2 < 0$.

4

What is the decision rule in the range  $\rho_1 > +1$?

Decision for  $m_0$  in the whole range.
Decision for  $m_1$  in the whole range.
Decision for  $m_0$  only if  $\rho_1 + \rho_2 < 0$.

5

What is the decision rule in the range  $\rho_1 < \, -1$?

Decision for  $m_0$  in the whole range.
Decision for  $m_1$  in the whole range.
Decision for  $m_0$  only if  $\rho_1 + \rho_2 < 0$.

6

What is the decision rule in the range  $\rho_2 > +1$?

Decision for  $m_0$  in the whole range.
Decision for  $m_1$  in the whole range.
Decision for  $m_0$  only if  $\rho_1 + \rho_2 < 0$.

7

What is the decision rule in the range  $\rho_2 < -1$?

Decision for  $m_0$  in the whole range.
Decision for  $m_1$  in the whole range.
Decision for  $m_0$  only if  $\rho_1 + \rho_2 < 0$.

8

Which of the following statements are true?

Variant  $\rm A$  leads to the minimum error probability.
Variant  $\rm B$  leads to the minimum error probability.
Variant  $\rm C$  leads to the minimum error probability.


Solution

(1)  Solutions 1 and 2  are correct:

  • The joint probability densities under conditions  $m_0$  and  $m_1$,  respectively,  are:
$$p_{\boldsymbol{ r} \hspace{0.05cm}|\hspace{0.05cm}m } ( \rho_{1},\rho_{2} |m_0 ) \hspace{-0.1cm} \ = \ \hspace{-0.1cm} {1}/{4} \cdot {\rm exp}\left [- | \rho_1 +1|- | \rho_2 +1| \hspace{0.05cm} \right ]\hspace{0.05cm},$$
$$p_{\boldsymbol{ r} \hspace{0.05cm}|\hspace{0.05cm}m } ( \rho_{1},\rho_{2} |m_1 ) \hspace{-0.1cm} \ = \ \hspace{-0.1cm} {1}/{4} \cdot {\rm exp}\left [- | \rho_1 -1|- | \rho_2 -1| \hspace{0.05cm} \right ]\hspace{0.05cm}.$$
  • For equally probable symbols   ⇒   ${\rm Pr}(m_0) = {\rm Pr}(m_1) = 0.5$,  the MAP decision rule is:   Decide for symbol  $m_0$    ⇔   signal  $s_0$,  if
$$p_{\boldsymbol{ r} \hspace{0.05cm}|\hspace{0.05cm}m } ( \rho_{1},\rho_{2} |m_0 ) > p_{\boldsymbol{ r} \hspace{0.05cm}|\hspace{0.05cm}m } (\rho_{1},\rho_{2} |m_1 ) \hspace{0.05cm}\hspace{0.3cm} \Rightarrow \hspace{0.3cm} {1}/{4} \cdot {\rm exp}\left [- | \rho_1 +1|- | \rho_2 +1| \hspace{0.05cm} \right ] > {1}/{4} \cdot {\rm exp}\left [- | \rho_1 -1|- | \rho_2 -1|\hspace{0.05cm} \right ] $$
$$\Rightarrow \hspace{0.3cm} | \rho_1 +1|+ | \rho_2 +1| < | \rho_1 -1|+ | \rho_2 -1|\hspace{0.3cm} \Rightarrow \hspace{0.3cm} L (\rho_1, \rho_2) = | \rho_1 +1|- | \rho_1 -1|+ | \rho_2 +1| - | \rho_2 -1| < 0 \hspace{0.05cm}.$$


(2)  All statements are true:

  • For $x ≥ 1$:
$$| x +1|- | x -1| = x +1 -x +1 =2 \hspace{0.05cm}.$$
  • Similarly,  for $x ≤ \, –1$,  e.g.  $x = \, –3$:
$$| x +1|- | x -1| = | -3 +1|- | -3 -1| = 2-4 = -2 \hspace{0.05cm}.$$
  • On the other hand,  in the middle range $–1 ≤ x ≤ +1$:
$$| x+1|- | x -1| = x +1 -1 +x =2x \hspace{0.05cm}.$$


(3)  Solution 1  is correct:

  • The result of subtask  (1)  was:  Decide for the symbol  $m_0$,  if
$$L (\rho_1, \rho_2) = | \rho_1 +1| - | \rho_1 -1|+ | \rho_2 +1| - | \rho_2 -1| < 0 \hspace{0.05cm}.$$
  • In the considered  (inner)  range  $-1 ≤ \rho_1 ≤ +1$,  $-1 ≤ \rho_2 ≤ +1$  holds with the result of subtask  (2):
$$| \rho_1+1| - | \rho_1 -1| = 2\rho_1 \hspace{0.05cm}, \hspace{0.2cm} | \rho_2+1| - | \rho_2 -1| = 2\rho_2 \hspace{0.05cm}.$$
  • If we insert this result above,  we have to decide for  $m_0$  exactly if
$$L (\rho_1, \rho_2) = 2 \cdot ( \rho_1+\rho_2) < 0 \hspace{0.3cm} \Rightarrow \hspace{0.3cm} \rho_1+\rho_2 < 0\hspace{0.05cm}.$$


(4)  Correct is here  solution 2:

  • For  $\rho_1 > 1$   ⇒   $|\rho_1+1| \, -|\rho_1 \, -1| = 2$,  while for  $D_2 = |\rho_2+1| \,-|\rho_2 \, -1|$   ⇒   all values between  $-2$  and  $+2$  are possible.
  • Thus,  the decision variable is  $L(\rho_1, \rho_2) = 2 + D_2 ≥ 0$.  In this case,  the rule leads to an  $m_1$  decision.


(5)  Solution 1  is correct:

  • After similar calculation as in subtask  (3),  one arrives at the result:
$$L (\rho_1, \rho_2) = -2 + D_2 \le 0 \hspace{0.3cm} \Rightarrow \hspace{0.3cm} {\rm decision\hspace{0.15cm} on\hspace{0.15cm}} m_0\hspace{0.05cm}.$$


(6)  Solution 2  is correct:  Decision on  $m_1$.

  • Similar to subtask  (4),  the following holds here:
$$D_1 = | \rho_1 +1| - | \rho_1 -1| \in \{-2, ... \hspace{0.05cm} , +2 \} \hspace{0.3cm} \Rightarrow \hspace{0.3cm}L (\rho_1, \rho_2) = 2 + D_1 \ge 0 \hspace{0.05cm}.$$


(7)  Solution 1  is correct:  Decision on  $m_0$.

  • After similar reasoning as in the last subtask,  we arrive at the result:
$$L (\rho_1, \rho_2) = -2 + D_1 \le 0 \hspace{0.3cm} \Rightarrow \hspace{0.3cm} {\rm decision\hspace{0.15cm} on\hspace{0.15cm}} m_0\hspace{0.05cm}.$$


Summary of the results

(8)  The results of subtasks  (3)  to  (7)  are summarized in the graph:

  • Subarea  $T_0$:   Decision on  $m_0$  or  $m_1$  according to task  (3).
  • Subarea  $T_1$:   Decision on  $m_1$  according to task  (4).
  • Subarea  $T_2$:   Decision on  $m_0$  according to task  (5).
  • Subarea  $T_3$:   Decision on  $m_1$  according to task  (6).
  • Subarea  $T_4$:   Decision on $m_0$  according to task  (7).
  • Subarea  $T_5$:   Decision on  $m_0$  according to task  (5), and on  $m_1$  according to task  (6)
    ⇒   For Laplace noise,  it does not matter whether one assigns  $T_5$  to region  $I_0$  or  $I_1$.
  • Subarea  $T_6$:   Again,  based on the results of task  (6)  and  (7),  one can assign this region to region  $I_0$  or region  $I_1$.


It can be seen:

  1. For subarea  $T_0$,  ... ,  $T_4$  there is a fixed assignment to the decision regions  $I_0$  (red)  and  $I_1$  (blue).
  2. In contrast,  the two yellow regions  $T_5$  and  $T_6$  can be assigned to both,  $I_0$  and  $I_1$  without loss of optimality.


Comparing this graph with variants  $\rm A$,  $\rm B$  and  $\rm C$  on the specification page,  we see that  suggestions 1 and 2  are correct:

  1. Variants  $\rm A$  and  $\rm B$ are equally good.  Both are optimal.  The error probability in both cases is  $p_{\rm min} = {\rm e}^{\rm -2}$.
  2. Variant  $\rm C$  is not optimal;  with respect to the subareas  $T_1$  and  $T_2$  there are mismatches.  The error probability is therefore greater than  $p_{\rm min}$.