Difference between revisions of "Aufgaben:Exercise 4.06: Optimal Decision Boundaries"

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For AWGN noise with variance  $\sigma_n^2$,  the decision boundary is the solution of the following vectorial equation with respect to the vector  $\boldsymbol{ \rho } =(\rho_1, \rho_2)$:
 
For AWGN noise with variance  $\sigma_n^2$,  the decision boundary is the solution of the following vectorial equation with respect to the vector  $\boldsymbol{ \rho } =(\rho_1, \rho_2)$:
 
:$$|| \boldsymbol{ s }_1||^2 - || \boldsymbol{ s }_0||^2 + 2 \cdot \sigma_n^2 \cdot  {\rm ln} \hspace{0.15cm} \frac{{\rm Pr}( m_0)}{{\rm Pr}( m_1)} =
 
:$$|| \boldsymbol{ s }_1||^2 - || \boldsymbol{ s }_0||^2 + 2 \cdot \sigma_n^2 \cdot  {\rm ln} \hspace{0.15cm} \frac{{\rm Pr}( m_0)}{{\rm Pr}( m_1)} =
2 \cdot \boldsymbol{ \rho }^{\rm T} \cdot (\boldsymbol{ s }_1 - \boldsymbol{ s }_0)\hspace{0.05cm},\hspace{0.2cm}
+
2 \cdot \boldsymbol{ \rho }^{\rm T} \cdot (\boldsymbol{ s }_1 - \boldsymbol{ s }_0)\hspace{0.05cm}.$$
\boldsymbol{ \rho } = (\rho_1 , \hspace{0.1cm}\rho_2 )\hspace{0.05cm}.$$
 
  
 
In addition,  two received values ​​
 
In addition,  two received values ​​
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===Solution===
 
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''  With ${\rm Pr}(m_0) = {\rm Pr}(m_1) = 0.5$, the equation of the boundary line between the decision areas $I_0$ and $I_1$ reads:
+
'''(1)'''  With  ${\rm Pr}(m_0) = {\rm Pr}(m_1) = 0.5$,  the equation of the boundary line between the decision areas  $I_0$  and  $I_1$  reads:
 
:$$|| \boldsymbol{ s }_1||^2 - || \boldsymbol{ s }_0||^2  =
 
:$$|| \boldsymbol{ s }_1||^2 - || \boldsymbol{ s }_0||^2  =
 
2 \cdot \boldsymbol{ \rho }^{\rm T} \cdot (\boldsymbol{ s }_1 - \boldsymbol{ s }_0)\hspace{0.05cm}.$$
 
2 \cdot \boldsymbol{ \rho }^{\rm T} \cdot (\boldsymbol{ s }_1 - \boldsymbol{ s }_0)\hspace{0.05cm}.$$
  
With the given vector values, i.e. the numerical values
+
*With the given vector values,  i.e. the numerical values
 
:$$|| \boldsymbol{ s }_1||^2  = 4^2 + 1^2 = 17\hspace{0.05cm}, \hspace{0.2cm}
 
:$$|| \boldsymbol{ s }_1||^2  = 4^2 + 1^2 = 17\hspace{0.05cm}, \hspace{0.2cm}
 
  || \boldsymbol{ s }_0||^2  =  1^2 + 5^2 = 26\hspace{0.05cm}, \hspace{0.2cm}
 
  || \boldsymbol{ s }_0||^2  =  1^2 + 5^2 = 26\hspace{0.05cm}, \hspace{0.2cm}
 
\boldsymbol{ s }_1 - \boldsymbol{ s }_0 = (3,\hspace{0.1cm}-4) \hspace{0.05cm}$$
 
\boldsymbol{ s }_1 - \boldsymbol{ s }_0 = (3,\hspace{0.1cm}-4) \hspace{0.05cm}$$
  
one obtains the following equation for the decision limits:
+
:one obtains the following equation for the decision limits:
 
:$$3 \cdot \rho_1 - 4 \cdot \rho_2  =  ({17-26})/{2} = -  {9}/{2}
 
:$$3 \cdot \rho_1 - 4 \cdot \rho_2  =  ({17-26})/{2} = -  {9}/{2}
 
\hspace{0.3cm}\Rightarrow \hspace{0.3cm}\rho_2  = 3/4 \cdot \rho_1 + 9/8
 
\hspace{0.3cm}\Rightarrow \hspace{0.3cm}\rho_2  = 3/4 \cdot \rho_1 + 9/8
 
\hspace{0.05cm}.$$
 
\hspace{0.05cm}.$$
  
[[File:P_ID2033__Dig_A_4_6a.png|right|frame|Decision line and decision regions for $K=0$]]
+
[[File:P_ID2033__Dig_A_4_6a.png|right|frame|Decision line and decision regions for  $K=0$]]
The decision limit lies in the middle between $s_0$ and $s_1$ and is rotated by $90^\circ$ compared to the connecting line between the two symbols. It goes through the point $(2.5, \ \,  3)$. So the <u>first solution</u> is correct.
+
*The decision line lies in the middle between&nbsp; $s_0$&nbsp; and&nbsp; $s_1$&nbsp; and is rotated by&nbsp; $90^\circ$&nbsp; compared to the connecting line between the two symbols.&nbsp; It goes through the point $(2.5, \ \,  3)$.&nbsp; So the&nbsp; <u>first solution</u>&nbsp; is correct.
 +
 
 +
*Solution 2,&nbsp; on the other hand,&nbsp; describes the connecting line itself and&nbsp; $\rho_2 = 3$&nbsp; is a horizontal line.
 +
 
  
Solution 2, on the other hand, describes the connecting line itself and $\rho_2 = 3$ is a horizontal line.
 
  
 +
'''(2)'''&nbsp; The decision region&nbsp; $I_1$&nbsp; should of course contain the point&nbsp; $s_1$ &nbsp; &#8658; &nbsp; region below the decision line.&nbsp;
 +
*Point $A = (1.5, \ \, 2)$&nbsp; belongs to this decision region,&nbsp; as shown in the graphic.
 +
*This can be shown mathematically,&nbsp; since the decision line goes through the point $(1.5, \ \, 2.25)$,&nbsp; for example,&nbsp; and thus&nbsp; $(1.5, \ \,  2)$&nbsp; lies below the decision line.
 +
*So,&nbsp; <u>solution 2</u>&nbsp; is correct.
  
'''(2)'''&nbsp; The decision area $I_1$ should of course contain the point $s_1$ &nbsp;&#8658;&nbsp; area below the decision line. Point $A = (1.5, \ \, 2)$ belongs to this decision domain, as shown in the graphic. This can be shown mathematically, since the decision line goes through the point $(1.5, \ \, 2.25)$, for example, and thus $(1.5, \ \,  2)$ lies below the decision line. So <u>solution 2</u> is correct.
 
  
  
'''(3)'''&nbsp; The decision line also goes through the point $(3, \ \,  3.375)$. $B = (3, \ \, 3.5)$ lies above and therefore belongs to the decision region $I_0$ according to <u>solution 1</u>.
+
'''(3)'''&nbsp; The decision line also goes through the point&nbsp; $(3, \ \,  3.375)$.  
 +
*$B = (3, \ \, 3.5)$&nbsp; lies above and therefore belongs to the decision region&nbsp; $I_0$&nbsp; according to&nbsp; <u>solution 1</u>.
  
  
'''(4)'''&nbsp; According to the equation in the information section and the calculations for subtask (1), the following now applies:
+
'''(4)'''&nbsp; According to the equation in the information section and the calculations for subtask&nbsp; '''(1)''',&nbsp; the following now applies:
[[File:P_ID2034__Dig_A_4_6c.png|right|frame|Decision areas for different $K$ values]]
+
[[File:P_ID2034__Dig_A_4_6c.png|right|frame|Decision regions for different&nbsp; $K$]]
 
:$$|| \boldsymbol{ s }_1||^2 - || \boldsymbol{ s }_0||^2 + 2 \cdot \sigma_n^2 \cdot  {\rm ln} \hspace{0.15cm} \frac{{\rm Pr}( m_0)}{{\rm Pr}( m_1)} =
 
:$$|| \boldsymbol{ s }_1||^2 - || \boldsymbol{ s }_0||^2 + 2 \cdot \sigma_n^2 \cdot  {\rm ln} \hspace{0.15cm} \frac{{\rm Pr}( m_0)}{{\rm Pr}( m_1)} =
 
2 \cdot \boldsymbol{ \rho }^{\rm T} \cdot (\boldsymbol{ s }_1 - \boldsymbol{ s }_0)\hspace{0.05cm}.$$
 
2 \cdot \boldsymbol{ \rho }^{\rm T} \cdot (\boldsymbol{ s }_1 - \boldsymbol{ s }_0)\hspace{0.05cm}.$$
  
With $|| \boldsymbol{ s }_1||^2 = 17$, $|| \boldsymbol{ s }_0||^2 = 26$, $ \boldsymbol{ s }_1 \, &ndash;\boldsymbol{ s }_0 = (3, \ \, &ndash;4)$ we obtain:
+
*With&nbsp; $|| \boldsymbol{ s }_1||^2 = 17$,&nbsp; $|| \boldsymbol{ s }_0||^2 = 26$,&nbsp; $ \boldsymbol{ s }_1 \, &ndash;\boldsymbol{ s }_0 = (3, \ \, &ndash;4)$&nbsp; we obtain:
 
:$$\rho_2  = 3/4 \cdot \rho_1 + 9/8 - K /8
 
:$$\rho_2  = 3/4 \cdot \rho_1 + 9/8 - K /8
 
\hspace{0.05cm}.$$
 
\hspace{0.05cm}.$$
  
The following abbreviation was used here:
+
*The following abbreviation was used here:
 
:$$K =  2 \cdot \sigma_n^2 \cdot  {\rm ln} \hspace{0.15cm} \frac{{\rm Pr}( m_0)}{{\rm Pr}( m_1)} =
 
:$$K =  2 \cdot \sigma_n^2 \cdot  {\rm ln} \hspace{0.15cm} \frac{{\rm Pr}( m_0)}{{\rm Pr}( m_1)} =
 
2 \cdot 1^2 \cdot 1.5 = 3 \hspace{0.05cm}.$$
 
2 \cdot 1^2 \cdot 1.5 = 3 \hspace{0.05cm}.$$
  
From this it follows:
+
*From this it follows:
 
:$$\rho_2  = 3/4 \cdot \rho_1 + 9/8 - 3 /8 = 3/4 \cdot \rho_1 + 3/4
 
:$$\rho_2  = 3/4 \cdot \rho_1 + 9/8 - 3 /8 = 3/4 \cdot \rho_1 + 3/4
 
\hspace{0.05cm}.$$
 
\hspace{0.05cm}.$$
  
The decision line is shifted down by $3/8$ (black curve, labeled "$K = 3$" in the graphic). So <u>solution 2</u> is correct.
+
*The decision line is shifted down by&nbsp; $3/8$&nbsp; $($black curve,&nbsp; labeled&nbsp; "$K = 3$"&nbsp; in the graphic$)$.&nbsp; So,&nbsp; <u>solution 2</u>&nbsp; is correct.
  
*The first equation describes the optimal decision boundary for equally probable symbols ($K = 0$, dashed gray).  
+
#The first equation describes the optimal decision line for equally probable symbols&nbsp; $(K = 0$,&nbsp; dashed gray$)$.  
*The third equation is valid for $K = \, &ndash;3$. This results with $\sigma_n^2 = 1$ for the symbol probabilities ${\rm Pr}(m_1) \approx 0.817$ and ${\rm Pr}(m_0) \approx 0.138$ (green curve).  
+
#The third equation is valid for&nbsp; $K = \, &ndash;3$.&nbsp; This results with&nbsp; $\sigma_n^2 = 1$&nbsp; for the symbol probabilities&nbsp; ${\rm Pr}(m_1) \approx 0.817$&nbsp; and&nbsp; ${\rm Pr}(m_0) \approx 0.138$&nbsp; (green curve).  
*The violet straight line results with $K = 9$, i.e. with the same probabilities as for the black curve, but now with the variance $\sigma_n^2 = 3$.
+
#The violet straight line results with&nbsp; $K = 9$,&nbsp; i.e. with the same probabilities as for the black curve,&nbsp; but now with the variance $\sigma_n^2 = 3$.
  
  
'''(5)'''&nbsp; The graphic above already shows that both $A$ and $B$ now belong to the decision regio $I_0$. <u>Solutions 1 and 3</u> are correct.
+
'''(5)'''&nbsp; The graphic above already shows that both&nbsp; $A$&nbsp; and&nbsp; $B$&nbsp; now belong to the decision region&nbsp; $I_0$.&nbsp; <u>Solutions 1 and 3</u>&nbsp; are correct.
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  

Revision as of 17:47, 27 July 2022

Signal space constellation with
$N = 2, \ M = 2$

We consider a binary transmission system  $(M = 2)$  that is defined by the drawn two-dimensional signal space constellation  $(N = 2)$.  The following applies to the two possible transmitted vectors that are directly coupled to the messages  $m_0$  and  $m_1$: 

$$\boldsymbol{ s }_0 \hspace{-0.1cm} \ =\ \hspace{-0.1cm} \sqrt {E} \cdot (1,\hspace{0.1cm} 5) \hspace{0.2cm} \Leftrightarrow \hspace{0.2cm} m_0 \hspace{0.05cm},$$
$$ \boldsymbol{ s }_1 \hspace{-0.1cm} \ =\ \hspace{-0.1cm} \sqrt {E} \cdot (4, \hspace{0.1cm}1) \hspace{0.2cm} \Leftrightarrow \hspace{0.2cm} m_1 \hspace{0.05cm}.$$

The optimal decision boundary between the regions  $I_0 ⇔ m_0$  and  $I_1 ⇔ m_1$ is sought.  The following assumptions are made:

  • It applies to subtasks  (1)  to  (3):
$${\rm Pr}(m_0 ) = {\rm Pr}(m_1 ) = 0.5 \hspace{0.05cm}. $$
  • For subtasks  (4)  and  (5)  should apply:
$${\rm Pr}(m_0 ) = 0.817 \hspace{0.05cm},\hspace{0.2cm} {\rm Pr}(m_1 ) = 0.183\hspace{0.3cm} \Rightarrow \hspace{0.3cm} {\rm ln} \hspace{0.15cm} \frac{{\rm Pr}( m_0)}{{\rm Pr}( m_1)} = 1.5 \hspace{0.05cm}.$$

For AWGN noise with variance  $\sigma_n^2$,  the decision boundary is the solution of the following vectorial equation with respect to the vector  $\boldsymbol{ \rho } =(\rho_1, \rho_2)$:

$$|| \boldsymbol{ s }_1||^2 - || \boldsymbol{ s }_0||^2 + 2 \cdot \sigma_n^2 \cdot {\rm ln} \hspace{0.15cm} \frac{{\rm Pr}( m_0)}{{\rm Pr}( m_1)} = 2 \cdot \boldsymbol{ \rho }^{\rm T} \cdot (\boldsymbol{ s }_1 - \boldsymbol{ s }_0)\hspace{0.05cm}.$$

In addition,  two received values ​​

$$\boldsymbol{ A }= \sqrt {E} \cdot (1.5, \hspace{0.1cm}2)\hspace{0.05cm},$$
$$\boldsymbol{ B }= \sqrt {E} \cdot (3, \hspace{0.1cm}3.5) $$

are drawn in the graphic.  It must be checked whether these should be assigned to the regions  $I_0$  $($and thus the message $m_0)$  or to  $I_1$  $($message $m_1)$  given the corresponding boundary conditions.


Notes:

  • For numeric calculations,  the energy  $E = 1$  can be set for simplification.


Questions

1

Where lies the optimal decision limit for equally probable symbols?  At

$\rho_2 = 3/4 \cdot \rho_1 + 9/8$,
$\rho_2 = \, –4/3 \cdot \rho_1 + 19/3$,
$\rho_2 = 3$.

2

To which decision area does the received value  $A = (1.5, \ \, 2)$  belong?

To decision area  $I_0$,
to decision area  $I_1$.

3

To which decision area does the received value  $B = (3, \ \, 3.5)$  belong?

To decision area  $I_0$,
to decision area  $I_1$.

4

What is the equation of the decision line for  ${\rm Pr}(m_0) = 0.817, \ \sigma_n = 1$?

$\rho_2 = 3/4 \cdot \rho_1 + 9/8$,
$\rho_2 = 3/4 \cdot \rho_1 + 3/4$,
$\rho_2 = 3/4 \cdot \rho_1 + 3/2$,
$\rho_2 = 3/4 \cdot \rho_1$.

5

Which decisions are made with these new regions  $I_0$  and  $I_1$? 

The received vector  $A$  is interpreted as message  $m_0$. 
The received vector  $A$  is interpreted as message  $m_1$. 
The received vector  $B$  is interpreted as message  $m_0$. 
The received vector  $B$  is interpreted as message  $m_1$. 


Solution

(1)  With  ${\rm Pr}(m_0) = {\rm Pr}(m_1) = 0.5$,  the equation of the boundary line between the decision areas  $I_0$  and  $I_1$  reads:

$$|| \boldsymbol{ s }_1||^2 - || \boldsymbol{ s }_0||^2 = 2 \cdot \boldsymbol{ \rho }^{\rm T} \cdot (\boldsymbol{ s }_1 - \boldsymbol{ s }_0)\hspace{0.05cm}.$$
  • With the given vector values,  i.e. the numerical values
$$|| \boldsymbol{ s }_1||^2 = 4^2 + 1^2 = 17\hspace{0.05cm}, \hspace{0.2cm} || \boldsymbol{ s }_0||^2 = 1^2 + 5^2 = 26\hspace{0.05cm}, \hspace{0.2cm} \boldsymbol{ s }_1 - \boldsymbol{ s }_0 = (3,\hspace{0.1cm}-4) \hspace{0.05cm}$$
one obtains the following equation for the decision limits:
$$3 \cdot \rho_1 - 4 \cdot \rho_2 = ({17-26})/{2} = - {9}/{2} \hspace{0.3cm}\Rightarrow \hspace{0.3cm}\rho_2 = 3/4 \cdot \rho_1 + 9/8 \hspace{0.05cm}.$$
Decision line and decision regions for  $K=0$
  • The decision line lies in the middle between  $s_0$  and  $s_1$  and is rotated by  $90^\circ$  compared to the connecting line between the two symbols.  It goes through the point $(2.5, \ \, 3)$.  So the  first solution  is correct.
  • Solution 2,  on the other hand,  describes the connecting line itself and  $\rho_2 = 3$  is a horizontal line.


(2)  The decision region  $I_1$  should of course contain the point  $s_1$   ⇒   region below the decision line. 

  • Point $A = (1.5, \ \, 2)$  belongs to this decision region,  as shown in the graphic.
  • This can be shown mathematically,  since the decision line goes through the point $(1.5, \ \, 2.25)$,  for example,  and thus  $(1.5, \ \, 2)$  lies below the decision line.
  • So,  solution 2  is correct.


(3)  The decision line also goes through the point  $(3, \ \, 3.375)$.

  • $B = (3, \ \, 3.5)$  lies above and therefore belongs to the decision region  $I_0$  according to  solution 1.


(4)  According to the equation in the information section and the calculations for subtask  (1),  the following now applies:

Decision regions for different  $K$
$$|| \boldsymbol{ s }_1||^2 - || \boldsymbol{ s }_0||^2 + 2 \cdot \sigma_n^2 \cdot {\rm ln} \hspace{0.15cm} \frac{{\rm Pr}( m_0)}{{\rm Pr}( m_1)} = 2 \cdot \boldsymbol{ \rho }^{\rm T} \cdot (\boldsymbol{ s }_1 - \boldsymbol{ s }_0)\hspace{0.05cm}.$$
  • With  $|| \boldsymbol{ s }_1||^2 = 17$,  $|| \boldsymbol{ s }_0||^2 = 26$,  $ \boldsymbol{ s }_1 \, –\boldsymbol{ s }_0 = (3, \ \, –4)$  we obtain:
$$\rho_2 = 3/4 \cdot \rho_1 + 9/8 - K /8 \hspace{0.05cm}.$$
  • The following abbreviation was used here:
$$K = 2 \cdot \sigma_n^2 \cdot {\rm ln} \hspace{0.15cm} \frac{{\rm Pr}( m_0)}{{\rm Pr}( m_1)} = 2 \cdot 1^2 \cdot 1.5 = 3 \hspace{0.05cm}.$$
  • From this it follows:
$$\rho_2 = 3/4 \cdot \rho_1 + 9/8 - 3 /8 = 3/4 \cdot \rho_1 + 3/4 \hspace{0.05cm}.$$
  • The decision line is shifted down by  $3/8$  $($black curve,  labeled  "$K = 3$"  in the graphic$)$.  So,  solution 2  is correct.
  1. The first equation describes the optimal decision line for equally probable symbols  $(K = 0$,  dashed gray$)$.
  2. The third equation is valid for  $K = \, –3$.  This results with  $\sigma_n^2 = 1$  for the symbol probabilities  ${\rm Pr}(m_1) \approx 0.817$  and  ${\rm Pr}(m_0) \approx 0.138$  (green curve).
  3. The violet straight line results with  $K = 9$,  i.e. with the same probabilities as for the black curve,  but now with the variance $\sigma_n^2 = 3$.


(5)  The graphic above already shows that both  $A$  and  $B$  now belong to the decision region  $I_0$.  Solutions 1 and 3  are correct.