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 entsprechenden 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>
{Welche der Entscheidungsregeln sind richtig? Entscheide für $m_0$, falls
+
{Which of the decision rules are correct?&nbsp; Decide for&nbsp; $m_0$,&nbsp; if
 
|type="[]"}
 
|type="[]"}
+ $\rho_{\it r|m}(\rho_1, \ \rho_2|m_0) > p_{\it r|m}(\rho_1, \ \rho_2|m_1)$,
+
+ $p_{\it r\hspace{0.03cm}|\hspace{0.03cm}m}(\rho_1, \ \rho_2\hspace{0.03cm}|\hspace{0.03cm}m_0) > p_{\it r\hspace{0.03cm}|\hspace{0.03cm}m}(\rho_1, \ \rho_2\hspace{0.03cm}|\hspace{0.03cm}m_1)$,
+ $L(\rho_1, \ \rho_2) = |\rho_1+1| \, &ndash;|\rho_1 \, &ndash;1| + |\rho_2+1| \, &ndash;|\rho_2 \, &ndash;1| < 0$,
+
+ $L(\rho_1, \ \rho_2) = |\rho_1+1| \, -|\rho_1 \, &ndash;1| + |\rho_2+1| \, -|\rho_2 \, &ndash;1| < 0$,
 
- $L(\rho_1, \ \rho_2) = \rho_1 + \rho_2 &#8805; 0$.
 
- $L(\rho_1, \ \rho_2) = \rho_1 + \rho_2 &#8805; 0$.
  
{Wie lässt sich der Ausdruck $|x+1| \ &ndash;|x \ &ndash;1|$ umformen?
+
{How can the expression&nbsp; $|x+1| \ -|x \ -1|$&nbsp; be transformed?
 
|type="[]"}
 
|type="[]"}
+ Für $x &#8805; 1$ ist $|x + 1| \, &ndash;|x \, &ndash;1| = 2$.
+
+ For&nbsp; $x &#8805; +1$:&nbsp; &nbsp; $|x + 1| \, -|x -1| = 2$.
+ Für $x &#8804; \, &ndash;1$ ist $|x+1| \, &ndash;|x \, &ndash;1| = \, &ndash;2$.
+
+ For&nbsp; $x &#8804; \, -1$:&nbsp; &nbsp; $|x+1| \,-|x \, -1| = \, -2$.
+ Für $&ndash;1 &#8804; x &#8804; 1$ ist $|x+1| \, &ndash;|x \, &ndash;1| = 2x$.
+
+ For&nbsp; $-1 &#8804; x &#8804; +1$:&nbsp; &nbsp; $|x+1| \, -|x \, -1| = 2x$.
  
{Wie lautet die Entscheidungsregel im Bereich $&ndash;1 &#8804; \rho_1 &#8804; +1$, $&ndash;1 &#8804; \rho_2 &#8804; +1$?
+
{What is the decision rule in the range&nbsp; $-1 &#8804; \rho_1 &#8804; +1$,&nbsp; $-1 &#8804; \rho_2 &#8804; +1$?
|type="[]"}
+
|type="()"}
+ Entscheidung für $m_0$, falls $\rho_1 + \rho_2 < 0$.
+
+ Decision for&nbsp; $m_0$,&nbsp; if&nbsp; $\rho_1 + \rho_2 < 0$.
- Entscheidung für $m_1$, falls $\rho_1 + \rho_2 < 0$.
+
- Decision for&nbsp; $m_1$,&nbsp; if&nbsp; $\rho_1 + \rho_2 < 0$.
  
{Wie lautet die Entscheidungsregel im Bereich $\rho_1 > +1$?
+
{What is the decision rule in the range&nbsp; $\rho_1 > +1$?
|type="[]"}
+
|type="()"}
- Entscheidung für $m_0$ im gesamten Bereich.
+
- Decision for&nbsp; $m_0$&nbsp; in the whole range.
+ Entscheidung für $m_1$ im gesamten Bereich.
+
+ Decision for&nbsp; $m_1$&nbsp; in the whole range.
- Entscheidung für $m_0$ nur, falls $\rho_1 + \rho_2 < 0$.
+
- Decision for&nbsp; $m_0$&nbsp; only if&nbsp; $\rho_1 + \rho_2 < 0$.
  
{Wie lautet die Entscheidungsregel im Bereich $\rho_1 < \, &ndash;1$?
+
{What is the decision rule in the range&nbsp; $\rho_1 < \, -1$?
|type="[]"}
+
|type="()"}
+ Entscheidung für $m_0$ im gesamten Bereich.
+
+ Decision for&nbsp; $m_0$&nbsp; in the whole range.
- Entscheidung für $m_1$ im gesamten Bereich.
+
- Decision for&nbsp; $m_1$&nbsp; in the whole range.
- Entscheidung für $m_0$ nur, falls $\rho_1 + \rho_2 < 0$.
+
- Decision for&nbsp; $m_0$&nbsp; only if&nbsp; $\rho_1 + \rho_2 < 0$.
  
{Wie lautet die Entscheidungsregel im Bereich $\rho_2 > +1$?
+
{What is the decision rule in the range&nbsp; $\rho_2 > +1$?
|type="[]"}
+
|type="()"}
- Entscheidung für $m_0$ im gesamten Bereich.
+
- Decision for&nbsp; $m_0$&nbsp; in the whole range.
+ Entscheidung für $m_1$ im gesamten Bereich.
+
+ Decision for&nbsp; $m_1$&nbsp; in the whole range.
- Entscheidung für $m_0$ nur, falls $\rho_1 + \rho_2 < 0$.
+
- Decision for&nbsp; $m_0$&nbsp; only if&nbsp; $\rho_1 + \rho_2 < 0$.
  
{Wie lautet die Entscheidungsregel im Bereich $\rho_2 < \, &ndash;1$?
+
{What is the decision rule in the range&nbsp; $\rho_2 < -1$?
|type="[]"}
+
|type="()"}
+ Entscheidung für $m_0$ im gesamten Bereich.
+
+ Decision for&nbsp; $m_0$&nbsp; in the whole range.
- Entscheidung für $m_1$ im gesamten Bereich.
+
- Decision for&nbsp; $m_1$&nbsp; in the whole range.
- Entscheidung für $m_0$ nur, falls $\rho_1 + \rho_2 < 0$.
+
- Decision for&nbsp; $m_0$&nbsp; only if&nbsp; $\rho_1 + \rho_2 < 0$.
  
{Welche der folgenden Aussagen sind zutreffend?
+
{Which of the following statements are true?
 
|type="[]"}
 
|type="[]"}
+ Die Variante <i>A</i> führt zur minimalen Fehlerwahrscheinlichkeit.
+
+ Variant &nbsp;$\rm A$&nbsp; leads to the minimum error probability.
+ Die Variante <i>B</i> führt zur minimalen Fehlerwahrscheinlichkeit.
+
+ Variant &nbsp;$\rm B$&nbsp; leads to the minimum error probability.
- Die Variante <i>C</i> führt zur minimalen Fehlerwahrscheinlichkeit.
+
- Variant &nbsp;$\rm C$&nbsp; leads to the minimum error probability.
 
</quiz>
 
</quiz>
  
===Musterlösung===
+
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''&nbsp; Die Verbundwahrscheinlichkeitsdichten unter den Bedingungen $m_0$ bzw. $m_1$ lauten:
+
'''(1)'''&nbsp; <u>Solutions 1 and 2</u>&nbsp; are correct:
 +
*The joint probability densities under conditions&nbsp; $m_0$&nbsp; and&nbsp; $m_1$,&nbsp; respectively,&nbsp; are:
 
:$$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 )  
 
\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},$$
 
\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 )  
 
:$$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}.$$
 
\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
Bei gleichwahrscheinlichen Symbolen &nbsp;&#8658;&nbsp; ${\rm Pr}(m_0) = {\rm Pr}(m_1) = 0.5$ lautet die MAP&ndash;Entscheidungsregel: Entscheide für das Symbol $m_0$ &nbsp;&#8660;&nbsp; Signal $s_0$, falls
 
 
:$$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}\hspace{0.3cm}
:$$\Rightarrow \hspace{0.3cm}  {1}/{4} \cdot  {\rm exp}\left [- | \rho_1 +1|- | \rho_2 +1| \hspace{0.05cm} \right ] >
+
\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 ] $$
 
   {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| <
 
:$$\Rightarrow \hspace{0.3cm}  | \rho_1 +1|+ | \rho_2 +1| <
   | \rho_1 -1|+ | \rho_2 -1|$$
+
   | \rho_1 -1|+ | \rho_2 -1|\hspace{0.3cm}
:$$\Rightarrow \hspace{0.3cm}  L (\rho_1, \rho_2) = | \rho_1 +1|-
+
\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}.$$
 
   | \rho_1 -1|+ | \rho_2 +1| - | \rho_2 -1| < 0 \hspace{0.05cm}.$$
  
Richtig sind demnach die <u>Lösungsvorschläge 1 und 2</u>.
 
  
 
+
'''(2)'''&nbsp; <u>All statements are true</u>:  
'''(2)'''&nbsp; <u>Alle Aussagen treffen zu</u>: Für $x &#8805; 1$ ist
+
*For $x &#8805; 1$:
 
:$$| x +1|- | x -1| = x +1 -x +1 =2 \hspace{0.05cm}.$$
 
:$$| x +1|- | x -1| = x +1 -x +1 =2 \hspace{0.05cm}.$$
  
Ebenso gilt für $x &#8804; \, &ndash;1$, zum Beispiel $x = \, &ndash;3$:
+
*Similarly,&nbsp; for $x &#8804; \, &ndash;1$,&nbsp; e.g.&nbsp; $x = \, &ndash;3$:
 
:$$| x +1|- | x -1| = | -3 +1|- | -3 -1| = 2-4 = -2 \hspace{0.05cm}.$$
 
:$$| x +1|- | x -1| = | -3 +1|- | -3 -1| = 2-4 = -2 \hspace{0.05cm}.$$
  
Dagegen gilt im mittleren Bereich $&ndash;1 &#8804; x &ndash; +1$:
+
*On the other hand,&nbsp; in the middle range $&ndash;1 &#8804; x &#8804; +1$:
 
:$$| x+1|- | x -1| = x +1 -1 +x =2x \hspace{0.05cm}.$$
 
:$$| x+1|- | x -1| = x +1 -1 +x =2x \hspace{0.05cm}.$$
  
  
'''(3)'''&nbsp; Das Ergebnis von Teilaufgabe (1) lautete: Entscheide für das Symbol $m_0$, falls
+
'''(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| -
 
:$$L (\rho_1, \rho_2) = | \rho_1 +1| -
 
   | \rho_1 -1|+ | \rho_2 +1| - | \rho_2 -1| < 0 \hspace{0.05cm}.$$
 
   | \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)''':
Im betrachteten (inneren) Bereich $&ndash;1 &#8804; \rho_1 &#8804; +1$, $&ndash;1 &#8804; \rho_2 &#8804; +1$ gilt mit dem Ergebnis der Teilaufgabe (2):
 
 
:$$| \rho_1+1| - | \rho_1 -1| = 2\rho_1 \hspace{0.05cm}, \hspace{0.2cm} | \rho_2+1| - | \rho_2 -1| = 2\rho_2 \hspace{0.05cm}.$$
 
:$$| \rho_1+1| - | \rho_1 -1| = 2\rho_1 \hspace{0.05cm}, \hspace{0.2cm} | \rho_2+1| - | \rho_2 -1| = 2\rho_2 \hspace{0.05cm}.$$
  
Setzt man dieses Ergebnis oben ein, so ist genau dann für $m_0$ zu entscheiden, falls
+
*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   
 
:$$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}.$$
 
  \hspace{0.3cm} \Rightarrow \hspace{0.3cm} \rho_1+\rho_2 < 0\hspace{0.05cm}.$$
  
Richtig ist also der <u>Lösungsvorschlag 1</u>.
 
  
 +
'''(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.
  
'''(4)'''&nbsp; Für $\rho_1 > 1$ ist $|\rho_1+1| \, &ndash;|\rho_1 \, &ndash;1| = 2$, während für $D_2 = |\rho_2+1| \, &ndash;|\rho_2 \, &ndash;1|$ alle Werte zwischen $&ndash;2$ und $+2$ möglich sind. Die Entscheidungsgröße ist somit $L(\rho_1, \rho_2) = 2 + D_2 &#8805; 0$. In diesem Fall führt die Regel zu einer $m_1$&ndash;Entscheidung. Richtig ist demnach hier der <u>Lösungsvorschlag 2</u>.
+
*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; Nach ähnlicher Rechnung wie in der Teilaufgabe (3) kommt man zum Ergebnis:
+
 
 +
'''(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}
 
:$$L (\rho_1, \rho_2) = -2 + D_2 \le 0  \hspace{0.3cm} \Rightarrow \hspace{0.3cm}
   {\rm Entscheidung\hspace{0.15cm} auf\hspace{0.15cm}} m_0\hspace{0.05cm},$$
+
   {\rm decision\hspace{0.15cm} on\hspace{0.15cm}} m_0\hspace{0.05cm}.$$
  
was dem <u>Lösungsvorschlag 1</u> entspricht.
 
  
 
+
'''(6)'''&nbsp; <u>Solution 2</u>&nbsp; is correct:&nbsp; Decision on&nbsp; $m_1$.
'''(6)'''&nbsp; Ähnlich der Teilaufgabe (4) gilt hier:
+
*Similar to subtask&nbsp; '''(4)''',&nbsp; the following holds here:
 
:$$D_1 = | \rho_1 +1| -    | \rho_1 -1| \in \{-2, ... \hspace{0.05cm} , +2 \}  
 
:$$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{0.3cm} \Rightarrow \hspace{0.3cm}L (\rho_1, \rho_2) = 2 + D_1 \ge 0
 
   \hspace{0.05cm}.$$
 
   \hspace{0.05cm}.$$
  
Richtig ist also hier der <u>Lösungsvorschlag 2</u>: Entscheidung auf $m_1$.
+
 
 +
'''(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:
 +
:$$L (\rho_1, \rho_2) = -2 + D_1 \le 0  \hspace{0.3cm} \Rightarrow \hspace{0.3cm}
 +
  {\rm decision\hspace{0.15cm} on\hspace{0.15cm}} m_0\hspace{0.05cm}.$$
  
  
'''(7)'''&nbsp; Nach ähnlicher Überlegung wie in der letzten Teilaufgabe kommt man zum Ergebnis:
+
[[File:P_ID2050__Dig_A_4_9h.png|right|frame|Summary of the results]]
:$$L (\rho_1, \rho_2) = -2 + D_1 \le 0  \hspace{0.3cm} \Rightarrow \hspace{0.3cm}
+
'''(8)'''&nbsp; The results of subtasks&nbsp; '''(3)'''&nbsp; to&nbsp; '''(7)'''&nbsp; are summarized in the graph:
  {\rm Entscheidung\hspace{0.15cm} auf\hspace{0.15cm}} m_0\hspace{0.05cm}.$$
 
  
Dies entspricht dem <u>Lösungsvorschlag 1</u>.
+
* 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; $I_1$.
  
  
'''(8)'''&nbsp; Die Ergebnisse der Teilaufgaben (3) bis (7) sind in der folgenden Grafik zusammengefasst:
+
It can be seen:
* <b>Teilgebiet <i>T_0</i>:</b> Entscheidung auf $m_0$ bzw. $m_1$ gemäß Aufgabe (3).
+
#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).
[[File:P_ID2050__Dig_A_4_9h.png|right|frame|Zusammenfassung der Ergebnisse]]
+
#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.
* <b>Teilgebiet <i>T_1</i> :</b> Entscheidung auf $m_1$ gemäß Aufgabe (4).
 
* <b>Teilgebiet <i>T_2</i> :</b> Entscheidung auf $m_0$ gemäß Aufgabe (5).
 
* <b>Teilgebiet <i>T_3</i> :</b> Entscheidung auf $m_1$ gemäß Aufgabe (6).
 
* <b>Teilgebiet <i>T_4</i> :</b> Entscheidung auf $m_0$ gemäß Aufgabe (7).
 
* <b>Teilgebiet <i>T_5</i> :</b> Nach dem Ergebnis von Aufgabe (5) sollte man auf $m_0$ entscheiden, nach Aufgabe (6) auf $m_1$. Das bedeutet: Bei Laplace&ndash;Rauschen ist es egal, ob man $T_5$ der Region $I_0$ oder $I_1$ zuordnet.
 
* <b>Teilgebiet <i>T_6</i> :</b> Auch dieses Gebiet kann man aufgrund der Ergebnisse von Aufgabe (4) und (7) sowohl der Region $I_0$ als uach der Region $I_1$ zuordnen.
 
  
  
Für die Teilaufgabe $T_0, \ ... \ , T_4$ gibt es eine feste Zuordnung zu den Entscheidungsregionen $I_0$ (rot) bzw. $I_1$ (blau). Dagegen können die beiden gelb markierten Bereiche $T_5$ und $T_6$ ohne Verlust an Optimalität sowohl $I_0$ als auch $I_1$ zugeordnet werden. Vergleicht man diese Grafik mit den Varianten <b><i>A, B</i></b> und <b><i>C</i></b> auf der Angabenseite, so erhält man das Ergebnis:
+
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:
* Die Varianten <b><i>A</i></b> und <b><i>B</i></b> sind gleich gut und beide sind optimal. Die Fehlerwahrscheinlichkeit ergibt sich in beiden Fällen zu $p_{\rm min} = {\rm e}^{\rm &ndash;2}$.
+
# 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; $p_{\rm min} = {\rm e}^{\rm -2}$.
* Die Variante <b><i>C</i></b> ist nicht optimal; bezüglich der Teilaufgabe $T_1$ und $T_2$ gibt es Fehlzuordnungen. Die Fehlerwahrscheinlichkeit ist demzufolge größer als $p_{\rm min}$. Richtig sind also die <u>Vorschläge 1 und 2</u>.
+
# 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; $p_{\rm min}$.  
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  
  
  
[[Category:Aufgaben zu Digitalsignalübertragung|^4.3 BER-Approximation^]]
+
[[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  $p_{\rm min}$.