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

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[[File:P_ID2015__Dig_A_4_6.png|right|frame|Signal space constellation with<br> $N = 2, \ M = 2$]]
 
[[File:P_ID2015__Dig_A_4_6.png|right|frame|Signal space constellation with<br> $N = 2, \ M = 2$]]
We consider a binary message system &nbsp;$(M = 2)$ that is defined by the drawn 2D signal space constellation &nbsp;$(N = 2)$.&nbsp; The following applies to the two possible transmitted vectors that are directly coupled to the messages&nbsp; $m_0$&nbsp; and&nbsp; $m_1$:&nbsp;  
+
We consider a binary transmission system &nbsp;$(M = 2)$&nbsp; that is defined by the drawn two-dimensional signal space constellation &nbsp;$(N = 2)$.&nbsp; The following applies to the two possible transmitted vectors that are directly coupled to the messages&nbsp; $m_0$&nbsp; and&nbsp; $m_1$:&nbsp;  
 
:$$\boldsymbol{ s }_0 \hspace{-0.1cm} \ =\ \hspace{-0.1cm}  \sqrt {E} \cdot (1,\hspace{0.1cm} 5) \hspace{0.2cm} \Leftrightarrow \hspace{0.2cm} m_0  \hspace{0.05cm},$$
 
:$$\boldsymbol{ s }_0 \hspace{-0.1cm} \ =\ \hspace{-0.1cm}  \sqrt {E} \cdot (1,\hspace{0.1cm} 5) \hspace{0.2cm} \Leftrightarrow \hspace{0.2cm} m_0  \hspace{0.05cm},$$
 
:$$ \boldsymbol{ s }_1 \hspace{-0.1cm} \ =\ \hspace{-0.1cm}  \sqrt {E} \cdot (4, \hspace{0.1cm}1) \hspace{0.2cm} \Leftrightarrow \hspace{0.2cm} m_1  \hspace{0.05cm}.$$
 
:$$ \boldsymbol{ s }_1 \hspace{-0.1cm} \ =\ \hspace{-0.1cm}  \sqrt {E} \cdot (4, \hspace{0.1cm}1) \hspace{0.2cm} \Leftrightarrow \hspace{0.2cm} m_1  \hspace{0.05cm}.$$
  
The optimal decision boundary between the regions&nbsp; $I_0 &#8660; m_0$&nbsp; and&nbsp; $I_1 &#8660; m_1$ is sought, whereby the following assumptions are made:
+
The optimal decision boundary between the regions&nbsp; $I_0 &#8660; m_0$&nbsp; and&nbsp; $I_1 &#8660; m_1$ is sought.&nbsp; The following assumptions are made:
* The following applies to subtasks '''(1)''' to '''(3)'''
+
* It applies to subtasks&nbsp; '''(1)'''&nbsp; to&nbsp; '''(3)''':
 
:$${\rm Pr}(m_0 ) = {\rm Pr}(m_1 ) = 0.5
 
:$${\rm Pr}(m_0 ) = {\rm Pr}(m_1 ) = 0.5
 
  \hspace{0.05cm}. $$
 
  \hspace{0.05cm}. $$
* For subtasks '''(4)''' and '''(5)''', on the other hand, the following should apply:
+
* For subtasks&nbsp; '''(4)'''&nbsp; and&nbsp; '''(5)'''&nbsp; should apply:
 
:$${\rm Pr}(m_0 ) = 0.817 \hspace{0.05cm},\hspace{0.2cm} {\rm Pr}(m_1 ) = 0.183\hspace{0.3cm}
 
:$${\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)} =
 
  \Rightarrow \hspace{0.3cm} {\rm ln} \hspace{0.15cm} \frac{{\rm Pr}( m_0)}{{\rm Pr}( m_1)} =
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\hspace{0.05cm}.$$
 
\hspace{0.05cm}.$$
  
For AWGN noise with variance&nbsp; $\sigma_n^2$,&nbsp; the decision limit is the solution of the following vectorial equation with respect to the vector&nbsp; $(\rho_1, \rho_2)$:
+
For AWGN noise with variance&nbsp; $\sigma_n^2$,&nbsp; the decision boundary is the solution of the following vectorial equation with respect to the vector&nbsp; $\boldsymbol{ \rho } =(\rho_1, \rho_2)$:
 
:$$|| \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},\hspace{0.2cm}
 
\boldsymbol{ \rho } = (\rho_1 , \hspace{0.1cm}\rho_2 )\hspace{0.05cm}.$$
 
\boldsymbol{ \rho } = (\rho_1 , \hspace{0.1cm}\rho_2 )\hspace{0.05cm}.$$
  
In addition, two received values ​​
+
In addition,&nbsp; two received values ​​
:$$\boldsymbol{ A }= \sqrt {E} \cdot (1.5, \hspace{0.1cm}2)\hspace{0.05cm}, \hspace{0.2cm} \boldsymbol{ B }= \sqrt {E} \cdot (3, \hspace{0.1cm}3.5)  $$
+
:$$\boldsymbol{ A }= \sqrt {E} \cdot (1.5, \hspace{0.1cm}2)\hspace{0.05cm},$$
 +
:$$\boldsymbol{ B }= \sqrt {E} \cdot (3, \hspace{0.1cm}3.5)  $$
  
are drawn in the graphic. It must be checked whether these should be assigned to the regions&nbsp; $I_0$&nbsp; $($and thus the message $m_0)$&nbsp; or&nbsp; $I_1$&nbsp; $($message $m_1)$&nbsp; given the corresponding boundary conditions.
+
are drawn in the graphic.&nbsp; It must be checked whether these should be assigned to the regions&nbsp; $I_0$&nbsp; $($and thus the message $m_0)$&nbsp; or to&nbsp; $I_1$&nbsp; $($message $m_1)$&nbsp; given the corresponding boundary conditions.
  
  
  
 
+
Notes:
 
+
* The exercise belongs to the chapter&nbsp; [[Digital_Signal_Transmission/Approximation_of_the_Error_Probability|"Approximation of the Error Probability"]].
''Notes:''
+
* The exercise belongs to the chapter&nbsp; [[Digital_Signal_Transmission/Approximation_of_the_Error_Probability|"Approximation of the Error Probability"]].  
+
* For numeric calculations,&nbsp; the energy&nbsp; $E = 1$&nbsp; can be set for simplification.
* For numeric calculations, the energy&nbsp; $E = 1$&nbsp; can be set for simplification.
 
 
   
 
   
  
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<quiz display=simple>
 
<quiz display=simple>
{Where lies the optimal decision limit for equally probable symbols? At  
+
{Where lies the optimal decision limit for equally probable symbols?&nbsp; At  
 
|type="[]"}
 
|type="[]"}
 
+ $\rho_2 = 3/4 \cdot \rho_1 + 9/8$,
 
+ $\rho_2 = 3/4 \cdot \rho_1 + 9/8$,
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- $\rho_2 = 3$.
 
- $\rho_2 = 3$.
  
{To which decision area does the received value&nbsp; $A = (1.5, \ \, 2)$ belong?
+
{To which decision area does the received value&nbsp; $A = (1.5, \ \, 2)$&nbsp; belong?
 
|type="()"}
 
|type="()"}
 
- To decision area&nbsp; $I_0$,
 
- To decision area&nbsp; $I_0$,
 
+ to decision area&nbsp; $I_1$.
 
+ to decision area&nbsp; $I_1$.
  
{To which decision area does the received value&nbsp; $B = (3, \ \, 3.5)$ belong?
+
{To which decision area does the received value&nbsp; $B = (3, \ \, 3.5)$&nbsp; belong?
 
|type="()"}
 
|type="()"}
 
+ To decision area&nbsp; $I_0$,
 
+ To decision area&nbsp; $I_0$,
 
- to decision area&nbsp; $I_1$.
 
- to decision area&nbsp; $I_1$.
  
{What is the equation of the decision line for&nbsp; ${\rm Pr}(m_0) = 0.817, \sigma_n = 1$?
+
{What is the equation of the decision line for&nbsp; ${\rm Pr}(m_0) = 0.817, \sigma_n = 1$?
 
|type="()"}
 
|type="()"}
 
- $\rho_2 = 3/4 \cdot \rho_1 + 9/8$,
 
- $\rho_2 = 3/4 \cdot \rho_1 + 9/8$,

Revision as of 16:50, 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  $\boldsymbol{ \rho } =(\rho_1, \rho_2)$:

$$|| \boldsymbol{ s }_1||^2 - || \boldsymbol{ s }_0||^2 + 2 \cdot \sigma_n^2 \cdot {\rm ln} \hspace{0.15cm} \frac{{\rm Pr}( m_0)}{{\rm Pr}( m_1)} = 2 \cdot \boldsymbol{ \rho }^{\rm T} \cdot (\boldsymbol{ s }_1 - \boldsymbol{ s }_0)\hspace{0.05cm},\hspace{0.2cm} \boldsymbol{ \rho } = (\rho_1 , \hspace{0.1cm}\rho_2 )\hspace{0.05cm}.$$

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 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 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 area $I_1$ should of course contain the point $s_1$  ⇒  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 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 areas for different $K$ values
$$|| \boldsymbol{ s }_1||^2 - || \boldsymbol{ s }_0||^2 + 2 \cdot \sigma_n^2 \cdot {\rm ln} \hspace{0.15cm} \frac{{\rm Pr}( m_0)}{{\rm Pr}( m_1)} = 2 \cdot \boldsymbol{ \rho }^{\rm T} \cdot (\boldsymbol{ s }_1 - \boldsymbol{ s }_0)\hspace{0.05cm}.$$

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.

  • The first equation describes the optimal decision boundary for equally probable symbols ($K = 0$, dashed gray).
  • 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).
  • 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 regio $I_0$. Solutions 1 and 3 are correct.