Difference between revisions of "Aufgaben:Exercise 4.10: Union Bound"

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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:EN_Dig_A_4_10.png|right|frame|Signal space constellations with $N=2$  and  $M=3$]]
 +
The so-called  "Union Bound"  gives an upper bound for the error probability of a non-binary transmission system  $(M > 2)$.  
  
 +
*The actual  (average)  error probability is generally given as follows:
 +
:$${\rm Pr}({ \cal E}) \hspace{-0.1cm} \ = \ \hspace{-0.1cm} \sum\limits_{i = 0 }^{M-1} {\rm Pr}(m_i) \cdot {\rm Pr}({ \cal E}\hspace{0.05cm}|\hspace{0.05cm} m_i ) \hspace{0.05cm},$$
 +
:$$ {\rm Pr}({ \cal E}\hspace{0.05cm}|\hspace{0.05cm} m_i ) \hspace{-0.1cm} \ = \ \hspace{-0.1cm} {\rm Pr} \left [ \bigcup_{k \ne i} { \cal E}_{ik}\right ] \hspace{0.05cm},\hspace{0.2cm}{ \rm where}\hspace{0.2cm}
 +
{ \cal E}_{ik}\text{:} \ \ \boldsymbol{ r }{\rm \hspace{0.15cm}is \hspace{0.15cm}closer \hspace{0.15cm}to \hspace{0.15cm}}\boldsymbol{ s }_k {\rm \hspace{0.15cm}than \hspace{0.15cm}to \hspace{0.15cm}the \hspace{0.15cm}setpoint \hspace{0.15cm}}\boldsymbol{ s }_i
 +
\hspace{0.05cm}.$$
  
 +
*The simpler  "Union Bound"  $\rm (UB)$  provides an upper bound on the falsification probability assuming that message  $m_i$  $($or signal  $\boldsymbol{s}_i)$  was sent:
 +
:$$p_{{\rm UB}\hspace{0.05cm}| \hspace{0.05cm}\boldsymbol{ s }_i} \hspace{-0.1cm} \ \ge \ \hspace{-0.1cm} {\rm Pr}({ \cal E}\hspace{0.05cm}|\hspace{0.05cm} \boldsymbol{ s }_i ) = {\rm Pr}({ \cal E}\hspace{0.05cm}|\hspace{0.05cm} m_i )\hspace{0.05cm},\ $$
 +
:$$ p_{{\rm UB}\hspace{0.05cm}| \hspace{0.05cm}\boldsymbol{ s }_i} \hspace{-0.1cm} \ = \ \hspace{-0.2cm}\sum\limits_{k = 0 ,\hspace{0.1cm}  k \ne i}^{M-1}\hspace{-0.1cm}
 +
{\rm Pr}({ \cal E}_{ik}) =  \hspace{-0.1cm}\sum\limits_{k = 0, \hspace{0.1cm} k \ne i}^{M-1}\hspace{-0.1cm}{\rm Q} \left ( \frac{d_{ik}/2}{\sigma_n} \right )\hspace{0.05cm}. $$
  
===Fragebogen===
+
The following abbreviations are used:
 +
* ${\rm Q}(x)$  is the complementary Gaussian error function;
 +
 
 +
* $d_{ik}$  denotes the distance between the signal points  $\boldsymbol{s}_i$  and $\boldsymbol{s}_k$;
 +
 
 +
* $\sigma_n$  is the rms value  (⇒ root of the variance)  of the additive white Gaussian noise.
 +
 
 +
 
 +
⇒   By averaging over all possible signals  $\boldsymbol{s}_i$,  we then arrive at the actual  "Union Bound":
 +
:$$p_{\rm UB} = \sum\limits_{i = 0 }^{M-1} {\rm Pr}(\boldsymbol{ s }_i) \cdot p_{{\rm UB}\hspace{0.05cm}| \hspace{0.05cm}\boldsymbol{ s }_i} \ge {\rm Pr}({ \cal E}) \hspace{0.05cm}.$$
 +
 
 +
*The graph shows three different signal space constellations, <br>each with&nbsp; $M = 3$&nbsp; signal space points&nbsp; $\boldsymbol{s}_0$,&nbsp; $\boldsymbol{s}_1$&nbsp; and&nbsp; $\boldsymbol{s}_2$&nbsp; in two-dimensional space &nbsp;$(N = 2)$.
 +
 +
*The basis functions&nbsp; $\varphi_1(t)$&nbsp; and&nbsp; $\varphi_2(t)$&nbsp; are suitably normalized.
 +
 
 +
*Thus,&nbsp; the signal space coordinates are also pure numerical values without unit:
 +
:$$\boldsymbol{ s }_1 = (-1, \hspace{0.1cm}+1)\hspace{0.05cm}, \hspace{0.2cm}
 +
  \boldsymbol{ s }_2 = (+1, \hspace{0.1cm}+1)\hspace{0.05cm}.$$
 +
 
 +
*The signal space point&nbsp; $\boldsymbol{s}_0$&nbsp; in configuration &nbsp;$\rm A$&nbsp; is located such that&nbsp; $\boldsymbol{s}_0$,&nbsp; $\boldsymbol{s}_1$,&nbsp; $\boldsymbol{s}_2$&nbsp; describe an equilateral triangle.
 +
 
 +
*In contrast,&nbsp; in configurations &nbsp;$\rm B$&nbsp; and  &nbsp;$\rm C$,&nbsp; &nbsp; $\boldsymbol{s}_0 = (0,\ 0)$&nbsp; resp.&nbsp; $\boldsymbol{s}_0 = (0, \ &ndash;1)$.
 +
 
 +
 
 +
 
 +
 
 +
 
 +
Notes:
 +
* The exercise belongs to the chapter&nbsp; [[Digital_Signal_Transmission/Approximation_of_the_Error_Probability|"Approximation of the Error Probability"]].
 +
 +
*Use the AWGN rms value &nbsp;$\sigma_n = 0.5$&nbsp; for all calculations.
 +
 +
* Given the following values of the complementary Gaussian error function:
 +
:$${\rm Q}(1) \hspace{-0.1cm} \ \approx \ \hspace{-0.1cm} 0.159\hspace{0.05cm}, \hspace{0.2cm}{\rm Q}(\sqrt{2}) \approx 0.079\hspace{0.05cm}, \hspace{0.23cm}{\rm Q}(\sqrt{3}) \approx 0.042\hspace{0.05cm},$$
 +
:$${\rm Q}(2) \hspace{-0.1cm} \ \approx \ \hspace{-0.1cm} 0.023\hspace{0.05cm}, \hspace{0.2cm}{\rm Q}(2.14) \approx 0.016\hspace{0.05cm}, \hspace{0.1cm}{\rm Q}(\sqrt{5}) \approx 0.013  \hspace{0.05cm}.$$
 +
 
 +
 
 +
 
 +
===Questions===
 
<quiz display=simple>
 
<quiz display=simple>
{Multiple-Choice
+
{Which of the three configurations leads to the smallest error probability&nbsp; $($at least according to the Union Bound approximation$)$?
|type="[]"}
+
|type="()"}
+ correct
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- Configuration &nbsp;$\rm A$,
- false
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- Configuration &nbsp;$\rm B$,
 +
+ Configuration &nbsp;$\rm C$.
 +
 
 +
{Calculate the&nbsp; "averaged Union Bound" &nbsp;$(p_{\rm UB})$&nbsp; for configuration &nbsp;$\rm A$.
 +
|type="{}"}
 +
$p_{\rm UB} \ = \ ${ 4.6 3% } $\ \%$
  
{Input-Box Frage
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{Calculate the&nbsp; "averaged Union Bound"&nbsp; for configuration &nbsp;$\rm B$.
 
|type="{}"}
 
|type="{}"}
$xyz \ = \ ${ 5.4 3% } $ab$
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$p_{\rm UB} \ = \ ${ 12.1 3% } $\ \%$
 +
 
 +
{Calculate the&nbsp; "averaged Union Bound"&nbsp; for configuration &nbsp;$\rm C$.
 +
|type="{}"}
 +
$p_{\rm UB} \ = \ ${ 3.2 3% } $\ \%$
 +
 
 +
{How would the noise rms value&nbsp; $\sigma_n$&nbsp; have to be changed for configuration &nbsp;$\rm A$&nbsp; to yield the same&nbsp; "Union Bound"&nbsp; as in subtask&nbsp; '''(4)'''?
 +
|type="{}"}
 +
$\sigma_n \ = \ ${ 0.467 3% }
 
</quiz>
 
</quiz>
  
===Musterlösung===
+
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''&nbsp;  
+
'''(1)'''&nbsp; Points&nbsp; $\boldsymbol{s}_1$&nbsp; and&nbsp; $\boldsymbol{s}_2$&nbsp; are the same for all configurations.
'''(2)'''&nbsp;  
+
*The smallest error probability occurs when&nbsp; $\boldsymbol{s}_0$&nbsp; is farthest from&nbsp; $\boldsymbol{s}_1$&nbsp; and&nbsp; $\boldsymbol{s}_2$.
'''(3)'''&nbsp;  
+
'''(4)'''&nbsp;  
+
*This is the case for configuration&nbsp; $\rm C$ &nbsp; &#8658; &nbsp; <u>solution 3</u>.
'''(5)'''&nbsp;  
+
 
 +
 
 +
 
 +
'''(2)'''&nbsp; For configuration&nbsp; $\rm A$,&nbsp; the distance between all points is the same:&nbsp; $d_{01} = d_{02} = d_{12} = 2$.
 +
*Therefore,&nbsp; to calculate the&nbsp; "Union Bound",&nbsp; it is not necessary to average over all symbols.&nbsp;
 +
 
 +
*And it is valid since e.g.&nbsp; $\boldsymbol{s}_0$&nbsp; is distorted into symbol&nbsp; $\boldsymbol{s}_1$&nbsp; or&nbsp; $\boldsymbol{s}_2$&nbsp; with equal probability:
 +
:$${\rm Pr}({ \cal E}) \le p_{\rm UB} = 2 \cdot {\rm Q} \left ( \frac{d_{ik}/2}{\sigma_n} \right ) = 2 \cdot {\rm Q}(2) \approx 2 \cdot 0.023 \hspace{0.1cm}\hspace{0.15cm}\underline {= 4.6\%} \hspace{0.05cm}. $$
 +
 
 +
 
 +
'''(3)'''&nbsp; Here,&nbsp; the falsification probabilities differ for each symbol.
 +
*If&nbsp; $\boldsymbol{s}_0$&nbsp; was sent,&nbsp; with $d_{01} = d_{02} = 2^{0.5}$&nbsp; and&nbsp; $\sigma = 0.5$:
 +
:$$p_{{\rm UB}\hspace{0.05cm}| \hspace{0.05cm}\boldsymbol{ s }_0} = 2 \cdot {\rm Q} \left ( \frac{\sqrt{2}/2}{0.5} \right )
 +
= 2 \cdot {\rm Q}(\sqrt{2}) = 2 \cdot 0.079 = 0.158 \hspace{0.05cm}. $$
 +
 
 +
*In contrast,&nbsp; the other two conditional probabilities are smaller:
 +
:$$p_{{\rm UB}\hspace{0.05cm}| \hspace{0.05cm}\boldsymbol{ s }_1} = p_{{\rm UB}\hspace{0.05cm}| \hspace{0.05cm}\boldsymbol{ s }_2} \hspace{-0.1cm} \ = \ \hspace{-0.1cm}
 +
{\rm Q} \left ( \frac{{2}/2}{0.5} \right )+{\rm Q} \left ( \frac{\sqrt{2}/2}{0.5} \right )= {\rm Q}(2) +{\rm Q}(\sqrt{2}) = 0.023 + 0.079 = 0.102 \hspace{0.05cm}.$$
 +
 
 +
*By averaging,&nbsp; we obtain for the Union Bound considering the different distances:
 +
:$$p_{\rm UB} \hspace{-0.1cm} \ = \ \hspace{-0.1cm} {1}/{3} \cdot \left [ p_{{\rm UB}\hspace{0.05cm}| \hspace{0.05cm}\boldsymbol{ s }_0} + p_{{\rm UB}\hspace{0.05cm}| \hspace{0.05cm}\boldsymbol{ s }_1} +p_{{\rm UB}\hspace{0.05cm}| \hspace{0.05cm}\boldsymbol{ s }_2}\right ]=
 +
{1}/{3} \cdot \left [ 2 \cdot  {\rm Q}(\sqrt{2})+ 2 \cdot ({\rm Q}({2}) + {\rm Q}(\sqrt{2})) \right ] =
 +
{1}/{3} \cdot \left [ 4 \cdot  {\rm Q}(\sqrt{2})+ 2 \cdot {\rm Q}({2})  \right ] $$
 +
:$$ \Rightarrow \hspace{0.3cm}  p_{\rm UB} =
 +
{1}/{3} \cdot \big [ 4 \cdot  0.079+ 2 \cdot 0.023  \big ] \hspace{0.1cm}\hspace{0.12cm}\underline {\approx 12.1\% }  \hspace{0.3cm}\Rightarrow \hspace{0.3cm}  p_{\rm UB}\ge {\rm Pr}({ \cal E})\hspace{0.05cm}.$$
 +
 
 +
 
 +
 
 +
'''(4)'''&nbsp; This configuration is described by the following equations:
 +
:$$d_{01} = d_{02} = \sqrt{2^2 + 1^2}= \sqrt{5} \approx 2.24\hspace{0.2cm}, d_{12} = 2$$
 +
:$$\Rightarrow \hspace{0.3cm}  p_{\rm UB}  =
 +
{1}/{3} \cdot \big [ 4 \cdot  {\rm Q}(\sqrt{5})+ 2 \cdot {\rm Q}({2})  \big ] = {1}/{3} \cdot \big [ 4 \cdot  0.013+ 2 \cdot 0.023  \big  ]\hspace{0.1cm}\hspace{0.15cm}\underline {\approx  3.2\%} \hspace{0.05cm}. $$
 +
 
 +
 
 +
'''(5)'''&nbsp; Let it be:
 +
:$$p_{\rm UB}  = 2 \cdot  {\rm Q}\left ( {1}/{\sigma_n} \right ) = 0.032 \hspace{0.3cm} \Rightarrow \hspace{0.3cm}
 +
{\rm Q}\left ( {1}/{\sigma_n} \right ) = 0.016\hspace{0.3cm} \Rightarrow \hspace{0.3cm} {1}/{\sigma_n} \approx 2.14
 +
\hspace{0.3cm} \Rightarrow \hspace{0.3cm}\hspace{0.1cm}\hspace{0.15cm}\sigma_n \hspace{0.15cm}\underline {\approx 0.467}\hspace{0.05cm}. $$
 
{{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 16:13, 6 September 2022

Signal space constellations with $N=2$  and  $M=3$

The so-called  "Union Bound"  gives an upper bound for the error probability of a non-binary transmission system  $(M > 2)$. 

  • The actual  (average)  error probability is generally given as follows:
$${\rm Pr}({ \cal E}) \hspace{-0.1cm} \ = \ \hspace{-0.1cm} \sum\limits_{i = 0 }^{M-1} {\rm Pr}(m_i) \cdot {\rm Pr}({ \cal E}\hspace{0.05cm}|\hspace{0.05cm} m_i ) \hspace{0.05cm},$$
$$ {\rm Pr}({ \cal E}\hspace{0.05cm}|\hspace{0.05cm} m_i ) \hspace{-0.1cm} \ = \ \hspace{-0.1cm} {\rm Pr} \left [ \bigcup_{k \ne i} { \cal E}_{ik}\right ] \hspace{0.05cm},\hspace{0.2cm}{ \rm where}\hspace{0.2cm} { \cal E}_{ik}\text{:} \ \ \boldsymbol{ r }{\rm \hspace{0.15cm}is \hspace{0.15cm}closer \hspace{0.15cm}to \hspace{0.15cm}}\boldsymbol{ s }_k {\rm \hspace{0.15cm}than \hspace{0.15cm}to \hspace{0.15cm}the \hspace{0.15cm}setpoint \hspace{0.15cm}}\boldsymbol{ s }_i \hspace{0.05cm}.$$
  • The simpler  "Union Bound"  $\rm (UB)$  provides an upper bound on the falsification probability assuming that message  $m_i$  $($or signal  $\boldsymbol{s}_i)$  was sent:
$$p_{{\rm UB}\hspace{0.05cm}| \hspace{0.05cm}\boldsymbol{ s }_i} \hspace{-0.1cm} \ \ge \ \hspace{-0.1cm} {\rm Pr}({ \cal E}\hspace{0.05cm}|\hspace{0.05cm} \boldsymbol{ s }_i ) = {\rm Pr}({ \cal E}\hspace{0.05cm}|\hspace{0.05cm} m_i )\hspace{0.05cm},\ $$
$$ p_{{\rm UB}\hspace{0.05cm}| \hspace{0.05cm}\boldsymbol{ s }_i} \hspace{-0.1cm} \ = \ \hspace{-0.2cm}\sum\limits_{k = 0 ,\hspace{0.1cm} k \ne i}^{M-1}\hspace{-0.1cm} {\rm Pr}({ \cal E}_{ik}) = \hspace{-0.1cm}\sum\limits_{k = 0, \hspace{0.1cm} k \ne i}^{M-1}\hspace{-0.1cm}{\rm Q} \left ( \frac{d_{ik}/2}{\sigma_n} \right )\hspace{0.05cm}. $$

The following abbreviations are used:

  • ${\rm Q}(x)$  is the complementary Gaussian error function;
  • $d_{ik}$  denotes the distance between the signal points  $\boldsymbol{s}_i$  and $\boldsymbol{s}_k$;
  • $\sigma_n$  is the rms value  (⇒ root of the variance)  of the additive white Gaussian noise.


⇒   By averaging over all possible signals  $\boldsymbol{s}_i$,  we then arrive at the actual  "Union Bound":

$$p_{\rm UB} = \sum\limits_{i = 0 }^{M-1} {\rm Pr}(\boldsymbol{ s }_i) \cdot p_{{\rm UB}\hspace{0.05cm}| \hspace{0.05cm}\boldsymbol{ s }_i} \ge {\rm Pr}({ \cal E}) \hspace{0.05cm}.$$
  • The graph shows three different signal space constellations,
    each with  $M = 3$  signal space points  $\boldsymbol{s}_0$,  $\boldsymbol{s}_1$  and  $\boldsymbol{s}_2$  in two-dimensional space  $(N = 2)$.
  • The basis functions  $\varphi_1(t)$  and  $\varphi_2(t)$  are suitably normalized.
  • Thus,  the signal space coordinates are also pure numerical values without unit:
$$\boldsymbol{ s }_1 = (-1, \hspace{0.1cm}+1)\hspace{0.05cm}, \hspace{0.2cm} \boldsymbol{ s }_2 = (+1, \hspace{0.1cm}+1)\hspace{0.05cm}.$$
  • The signal space point  $\boldsymbol{s}_0$  in configuration  $\rm A$  is located such that  $\boldsymbol{s}_0$,  $\boldsymbol{s}_1$,  $\boldsymbol{s}_2$  describe an equilateral triangle.
  • In contrast,  in configurations  $\rm B$  and  $\rm C$,    $\boldsymbol{s}_0 = (0,\ 0)$  resp.  $\boldsymbol{s}_0 = (0, \ –1)$.



Notes:

  • Use the AWGN rms value  $\sigma_n = 0.5$  for all calculations.
  • Given the following values of the complementary Gaussian error function:
$${\rm Q}(1) \hspace{-0.1cm} \ \approx \ \hspace{-0.1cm} 0.159\hspace{0.05cm}, \hspace{0.2cm}{\rm Q}(\sqrt{2}) \approx 0.079\hspace{0.05cm}, \hspace{0.23cm}{\rm Q}(\sqrt{3}) \approx 0.042\hspace{0.05cm},$$
$${\rm Q}(2) \hspace{-0.1cm} \ \approx \ \hspace{-0.1cm} 0.023\hspace{0.05cm}, \hspace{0.2cm}{\rm Q}(2.14) \approx 0.016\hspace{0.05cm}, \hspace{0.1cm}{\rm Q}(\sqrt{5}) \approx 0.013 \hspace{0.05cm}.$$


Questions

1

Which of the three configurations leads to the smallest error probability  $($at least according to the Union Bound approximation$)$?

Configuration  $\rm A$,
Configuration  $\rm B$,
Configuration  $\rm C$.

2

Calculate the  "averaged Union Bound"  $(p_{\rm UB})$  for configuration  $\rm A$.

$p_{\rm UB} \ = \ $

$\ \%$

3

Calculate the  "averaged Union Bound"  for configuration  $\rm B$.

$p_{\rm UB} \ = \ $

$\ \%$

4

Calculate the  "averaged Union Bound"  for configuration  $\rm C$.

$p_{\rm UB} \ = \ $

$\ \%$

5

How would the noise rms value  $\sigma_n$  have to be changed for configuration  $\rm A$  to yield the same  "Union Bound"  as in subtask  (4)?

$\sigma_n \ = \ $


Solution

(1)  Points  $\boldsymbol{s}_1$  and  $\boldsymbol{s}_2$  are the same for all configurations.

  • The smallest error probability occurs when  $\boldsymbol{s}_0$  is farthest from  $\boldsymbol{s}_1$  and  $\boldsymbol{s}_2$.
  • This is the case for configuration  $\rm C$   ⇒   solution 3.


(2)  For configuration  $\rm A$,  the distance between all points is the same:  $d_{01} = d_{02} = d_{12} = 2$.

  • Therefore,  to calculate the  "Union Bound",  it is not necessary to average over all symbols. 
  • And it is valid since e.g.  $\boldsymbol{s}_0$  is distorted into symbol  $\boldsymbol{s}_1$  or  $\boldsymbol{s}_2$  with equal probability:
$${\rm Pr}({ \cal E}) \le p_{\rm UB} = 2 \cdot {\rm Q} \left ( \frac{d_{ik}/2}{\sigma_n} \right ) = 2 \cdot {\rm Q}(2) \approx 2 \cdot 0.023 \hspace{0.1cm}\hspace{0.15cm}\underline {= 4.6\%} \hspace{0.05cm}. $$


(3)  Here,  the falsification probabilities differ for each symbol.

  • If  $\boldsymbol{s}_0$  was sent,  with $d_{01} = d_{02} = 2^{0.5}$  and  $\sigma = 0.5$:
$$p_{{\rm UB}\hspace{0.05cm}| \hspace{0.05cm}\boldsymbol{ s }_0} = 2 \cdot {\rm Q} \left ( \frac{\sqrt{2}/2}{0.5} \right ) = 2 \cdot {\rm Q}(\sqrt{2}) = 2 \cdot 0.079 = 0.158 \hspace{0.05cm}. $$
  • In contrast,  the other two conditional probabilities are smaller:
$$p_{{\rm UB}\hspace{0.05cm}| \hspace{0.05cm}\boldsymbol{ s }_1} = p_{{\rm UB}\hspace{0.05cm}| \hspace{0.05cm}\boldsymbol{ s }_2} \hspace{-0.1cm} \ = \ \hspace{-0.1cm} {\rm Q} \left ( \frac{{2}/2}{0.5} \right )+{\rm Q} \left ( \frac{\sqrt{2}/2}{0.5} \right )= {\rm Q}(2) +{\rm Q}(\sqrt{2}) = 0.023 + 0.079 = 0.102 \hspace{0.05cm}.$$
  • By averaging,  we obtain for the Union Bound considering the different distances:
$$p_{\rm UB} \hspace{-0.1cm} \ = \ \hspace{-0.1cm} {1}/{3} \cdot \left [ p_{{\rm UB}\hspace{0.05cm}| \hspace{0.05cm}\boldsymbol{ s }_0} + p_{{\rm UB}\hspace{0.05cm}| \hspace{0.05cm}\boldsymbol{ s }_1} +p_{{\rm UB}\hspace{0.05cm}| \hspace{0.05cm}\boldsymbol{ s }_2}\right ]= {1}/{3} \cdot \left [ 2 \cdot {\rm Q}(\sqrt{2})+ 2 \cdot ({\rm Q}({2}) + {\rm Q}(\sqrt{2})) \right ] = {1}/{3} \cdot \left [ 4 \cdot {\rm Q}(\sqrt{2})+ 2 \cdot {\rm Q}({2}) \right ] $$
$$ \Rightarrow \hspace{0.3cm} p_{\rm UB} = {1}/{3} \cdot \big [ 4 \cdot 0.079+ 2 \cdot 0.023 \big ] \hspace{0.1cm}\hspace{0.12cm}\underline {\approx 12.1\% } \hspace{0.3cm}\Rightarrow \hspace{0.3cm} p_{\rm UB}\ge {\rm Pr}({ \cal E})\hspace{0.05cm}.$$


(4)  This configuration is described by the following equations:

$$d_{01} = d_{02} = \sqrt{2^2 + 1^2}= \sqrt{5} \approx 2.24\hspace{0.2cm}, d_{12} = 2$$
$$\Rightarrow \hspace{0.3cm} p_{\rm UB} = {1}/{3} \cdot \big [ 4 \cdot {\rm Q}(\sqrt{5})+ 2 \cdot {\rm Q}({2}) \big ] = {1}/{3} \cdot \big [ 4 \cdot 0.013+ 2 \cdot 0.023 \big ]\hspace{0.1cm}\hspace{0.15cm}\underline {\approx 3.2\%} \hspace{0.05cm}. $$


(5)  Let it be:

$$p_{\rm UB} = 2 \cdot {\rm Q}\left ( {1}/{\sigma_n} \right ) = 0.032 \hspace{0.3cm} \Rightarrow \hspace{0.3cm} {\rm Q}\left ( {1}/{\sigma_n} \right ) = 0.016\hspace{0.3cm} \Rightarrow \hspace{0.3cm} {1}/{\sigma_n} \approx 2.14 \hspace{0.3cm} \Rightarrow \hspace{0.3cm}\hspace{0.1cm}\hspace{0.15cm}\sigma_n \hspace{0.15cm}\underline {\approx 0.467}\hspace{0.05cm}. $$