Difference between revisions of "Aufgaben:Exercise 1.16: Block Error Probability Bounds for AWGN"

From LNTwww
Line 1: Line 1:
 
{{quiz-Header|Buchseite=Channel_Coding/Limits_for_Block_Error_Probability}}
 
{{quiz-Header|Buchseite=Channel_Coding/Limits_for_Block_Error_Probability}}
  
[[File:P_ID2414__KC_A_1_15.png|right|frame|Error function  ${\rm Q}(x)$  and approximations ]]
+
[[File:P_ID2414__KC_A_1_15.png|right|frame|Function&nbsp; ${\rm Q}(x)$&nbsp; and approximations;<br>it holds:&nbsp; ${\rm Q_u}(x)\le{\rm Q}(x)\le{\rm Q_o}(x)$ ]]
  
 
We assume the following constellation:
 
We assume the following constellation:
*a linear block code with code rate&nbsp; $R = k/n$&nbsp; and distance spectrum&nbsp; $\{W_i\}, \ i = 1, \ \text{...} \ , n$,
+
*A linear block code with code rate&nbsp; $R = k/n$&nbsp; and distance spectrum&nbsp; $\{W_i\}, \ i = 1, \ \text{...} \ , n$,
 +
 
 
*an AWGN channel characterized by&nbsp; $E_{\rm B}/N_{0}$ &nbsp; ⇒ &nbsp; convertible to noise power&nbsp; $\sigma^2$,
 
*an AWGN channel characterized by&nbsp; $E_{\rm B}/N_{0}$ &nbsp; ⇒ &nbsp; convertible to noise power&nbsp; $\sigma^2$,
*a receiver based on ''soft decision'' as well as the ''maximum likelihood criterion''.
+
 
 +
*a receiver based on&nbsp; "soft decision"&nbsp; as well as the&nbsp; "maximum likelihood criterion".
  
  
Under the assumption valid for the entire exercise that always the null word&nbsp; $\underline{x}_{1} = (0, 0, \text{... } \ , 0)$&nbsp; is sent, the&nbsp; [[Channel_Coding/Limits_for_Block_Error_Probability#Union_Bound_of_the_block_error_probability|"pairwise error probability"]] with a different codeword&nbsp; $\underline{x}_{l} (l = 2,\ \text{...} \ , 2^k)$:
+
Under the assumption valid for the entire exercise that always the zero-word&nbsp; $\underline{x}_{1} = (0, 0, \text{... } \ , 0)$&nbsp; is sent, the&nbsp; [[Channel_Coding/Limits_for_Block_Error_Probability#Union_Bound_of_the_block_error_probability|"pairwise error probability"]]&nbsp; with a different code word&nbsp; $\underline{x}_{l} (l = 2,\ \text{...} \ , 2^k)$:
  
 
:$$ {\rm Pr}[\hspace{0.05cm}\underline{x}_{\hspace{0.02cm}1} \hspace{-0.02cm}\mapsto \hspace{-0.02cm}\underline{x}_{\hspace{0.02cm}l}\hspace{0.05cm}] = {\rm Q}\left ( \sqrt{w_{\rm H}(\underline{x}_{\hspace{0.02cm}l})/\sigma^2} \right ) \hspace{0.05cm}.$$
 
:$$ {\rm Pr}[\hspace{0.05cm}\underline{x}_{\hspace{0.02cm}1} \hspace{-0.02cm}\mapsto \hspace{-0.02cm}\underline{x}_{\hspace{0.02cm}l}\hspace{0.05cm}] = {\rm Q}\left ( \sqrt{w_{\rm H}(\underline{x}_{\hspace{0.02cm}l})/\sigma^2} \right ) \hspace{0.05cm}.$$
 
   
 
   
The derivation of this relation can be found in [Liv10]. Used in this equation are:
+
The derivation of this relation can be found in&nbsp; [Liv10].&nbsp; Used in this equation are:
 
*the&nbsp; [[Theory_of_Stochastic_Signals/Gaussian_Distributed_Random_Variables#Exceedance_probability|"complementary Gaussian error function"]]&nbsp; ${\rm Q}(x)$,
 
*the&nbsp; [[Theory_of_Stochastic_Signals/Gaussian_Distributed_Random_Variables#Exceedance_probability|"complementary Gaussian error function"]]&nbsp; ${\rm Q}(x)$,
*the&nbsp; [[Channel_Coding/Objective_of_Channel_Coding#Important_definitions_for_block_coding|"Hamming weight"]]&nbsp; $w_{\rm H}(\underline{x}_{l})$&nbsp; of the codeword&nbsp; $\underline{x}_{l}$,
+
 
*the&nbsp; [[Digital_Signal_Transmission/Optimization_of_Baseband_Transmission_Systems#System_optimization_with_power_limitation|"AWGN noise power"]]&nbsp; $\sigma^2 = (2 - R - E_{\rm B}/N_{0})^{-1}.$  
+
*the&nbsp; [[Channel_Coding/Objective_of_Channel_Coding#Important_definitions_for_block_coding|"Hamming weight"]]&nbsp; $w_{\rm H}(\underline{x}_{l})$&nbsp; of the code word&nbsp; $\underline{x}_{l}$,
 +
 
 +
*the&nbsp; [[Digital_Signal_Transmission/Optimization_of_Baseband_Transmission_Systems#System_optimization_with_power_limitation|"AWGN noise power"]]&nbsp; $\sigma^2 = (2 \cdot R \cdot E_{\rm B}/N_{0})^{-1}.$  
  
  
Damit lassen sich verschiedene Schranken für die Blockfehlerwahrscheinlichkeit angeben:
+
This allows various bounds to be specified for the block error probability:
  
*the so called&nbsp; [[Channel_Coding/Limits_for_Block_Error_Probability#Union_Bound_of_the_block_error_probability|"Union Bound"]]&nbsp; (UB):
+
*the so called&nbsp; [[Channel_Coding/Limits_for_Block_Error_Probability#Union_Bound_of_the_block_error_probability|"Union Bound"]]&nbsp; $\rm (UB)$:
 
   
 
   
 
:$$p_1 = \sum_{l = 2}^{2^k}\hspace{0.05cm}{\rm Pr}[\hspace{0.05cm}\underline{x}_{\hspace{0.02cm}1} \hspace{-0.02cm}\mapsto \hspace{-0.02cm}\underline{x}_{\hspace{0.02cm}l}\hspace{0.05cm}] = \sum_{l \hspace{0.05cm}= \hspace{0.05cm}2}^{2^k}\hspace{0.05cm}{\rm Q}\left ( \sqrt{w_{\rm H}(\underline{x}_{\hspace{0.02cm}l})/\sigma^2} \right ) \hspace{0.05cm},$$
 
:$$p_1 = \sum_{l = 2}^{2^k}\hspace{0.05cm}{\rm Pr}[\hspace{0.05cm}\underline{x}_{\hspace{0.02cm}1} \hspace{-0.02cm}\mapsto \hspace{-0.02cm}\underline{x}_{\hspace{0.02cm}l}\hspace{0.05cm}] = \sum_{l \hspace{0.05cm}= \hspace{0.05cm}2}^{2^k}\hspace{0.05cm}{\rm Q}\left ( \sqrt{w_{\rm H}(\underline{x}_{\hspace{0.02cm}l})/\sigma^2} \right ) \hspace{0.05cm},$$
  
*the so called&nbsp; [[Channel_Coding/Limits_for_Block_Error_Probability#Bounds_for_the_.287.2C_4.2C_3.29_Hamming_code_at_the_AWGN_channel|"Truncated Union Bound"]]&nbsp; (TUB):
+
*the so called&nbsp; [[Channel_Coding/Limits_for_Block_Error_Probability#Bounds_for_the_.287.2C_4.2C_3.29_Hamming_code_at_the_AWGN_channel|"Truncated Union Bound"]]&nbsp; $\rm  (TUB)$:
 
   
 
   
 
:$$p_2 = W_{d_{\rm min}} \cdot {\rm Q}\left ( \sqrt{d_{\rm min}/\sigma^2} \right ) \hspace{0.05cm},$$
 
:$$p_2 = W_{d_{\rm min}} \cdot {\rm Q}\left ( \sqrt{d_{\rm min}/\sigma^2} \right ) \hspace{0.05cm},$$
  
*the&nbsp; [[Channel_Coding/Limits_for_Block_Error_Probability#The_upper_bound_according_to_Bhattacharyya|"Bhattacharyya bound"]]:
+
*the&nbsp; [[Channel_Coding/Limits_for_Block_Error_Probability#The_upper_bound_according_to_Bhattacharyya|"Bhattacharyya Bound"]]:
 
   
 
   
:$$p_3 = W(\beta) - 1\hspace{0.05cm},\hspace{0.2cm} {\rm mit}\hspace{0.15cm} \beta = {\rm e}^{ - 1/(2\sigma^2) } \hspace{0.05cm}.$$
+
:$$p_3 = W(\beta) - 1\hspace{0.05cm},\hspace{0.2cm} {\rm with}\hspace{0.15cm} \beta = {\rm e}^{ - 1/(2\sigma^2) } \hspace{0.05cm}.$$
  
:In this case, replace the distance spectrum&nbsp; $\{W_i\}$&nbsp; with the weight enumerator function:
+
:In this case,&nbsp; replace the distance spectrum&nbsp; $\{W_i\}$&nbsp; with the weight enumerator function:
  
 
:$$\left \{ \hspace{0.05cm} W_i \hspace{0.05cm} \right \} \hspace{0.3cm} \Leftrightarrow \hspace{0.3cm} W(X) = \sum_{i=0 }^{n} W_i \cdot X^{i} = W_0 + W_1 \cdot X + W_2 \cdot X^{2} + ... \hspace{0.05cm} + W_n \cdot X^{n}\hspace{0.05cm}.$$
 
:$$\left \{ \hspace{0.05cm} W_i \hspace{0.05cm} \right \} \hspace{0.3cm} \Leftrightarrow \hspace{0.3cm} W(X) = \sum_{i=0 }^{n} W_i \cdot X^{i} = W_0 + W_1 \cdot X + W_2 \cdot X^{2} + ... \hspace{0.05cm} + W_n \cdot X^{n}\hspace{0.05cm}.$$
 
   
 
   
In the transition from the ''Union Bound''&nbsp; $p_{1}$&nbsp; to the more imprecise bound&nbsp; $p_{3}$&nbsp; among others the function&nbsp; ${\rm Q}(x)$&nbsp; is replaced by the&nbsp; [https://en.wikipedia.org/wiki/Chernoff_bound Chernoff-Rubin bound]&nbsp; ${\rm Q}_{\rm CR}(x)$&nbsp;. Both functions are shown in the above graph (red and green curve, respectively).
+
In the transition from the&nbsp; "Union Bound"&nbsp; $p_{1}$&nbsp; to the more imprecise bound&nbsp; $p_{3}$&nbsp; among others  
 +
*the function&nbsp; ${\rm Q}(x)$&nbsp; is replaced by the&nbsp; [https://en.wikipedia.org/wiki/Chernoff_bound "Chernoff-Rubin bound"]&nbsp; ${\rm Q}_{\rm CR}(x)$.  
 +
 
 +
*Both functions are shown in the above graph&nbsp; (red and green curve, resp.).
 +
 
  
In the&nbsp; [[Aufgaben:Exercise_1.16Z:_Bounds_for_the_Gaussian_Error_Function|"Exercise 1.16Z"]]&nbsp; the relationship between these functions is evaluated numerically and referenced to the bounds&nbsp; ${\rm Q}_{o}(x)$ and ${\rm Q}_{u}(x)$&nbsp; which are also drawn in the above graph.
+
In the&nbsp; [[Aufgaben:Exercise_1.16Z:_Bounds_for_the_Gaussian_Error_Function|"Exercise 1.16Z"]]&nbsp; the relationship between these functions is evaluated numerically and referenced to the bounds&nbsp; ${\rm Q}_{\rm o}(x)$ and ${\rm Q}_{\rm u}(x)$&nbsp; which are also drawn in the above graph.
  
  
Line 46: Line 54:
 
Hints:  
 
Hints:  
 
* This exercise belongs to the chapter&nbsp; [[Channel_Coding/Schranken_für_die_Blockfehlerwahrscheinlichkeit|"Block error probability bounds"]].
 
* This exercise belongs to the chapter&nbsp; [[Channel_Coding/Schranken_für_die_Blockfehlerwahrscheinlichkeit|"Block error probability bounds"]].
* The above cited reference [Liv10] refers to the lecture manuscript "Liva, G.: ''Channel Coding''.  Chair of Communications Engineering, TU Munich and DLR Oberpfaffenhofen, 2010."
+
 
 +
* The above cited reference&nbsp; "[Liv10]"&nbsp; refers to the lecture manuscript "Liva, G.:&nbsp; Channel Coding.&nbsp; Chair of Communications Engineering, TU Munich and DLR Oberpfaffenhofen, 2010."
 +
 
 
* Further we refer to the interactive applet&nbsp; [[Applets:Komplementäre_Gaußsche_Fehlerfunktionen| "Complementary Gaussian error functions"]].
 
* Further we refer to the interactive applet&nbsp; [[Applets:Komplementäre_Gaußsche_Fehlerfunktionen| "Complementary Gaussian error functions"]].
  
Line 56: Line 66:
  
 
<quiz display=simple>
 
<quiz display=simple>
{Which equation applies to the ''Union Bound''?
+
{Which equation applies to the&nbsp; "Union Bound"?
 
|type="[]"}
 
|type="[]"}
 
- $p_{1} = \sum_{l\hspace{0.05cm}=\hspace{0.05cm}2}^{2^k} W_{l} · {\rm Q}\big[(l/\sigma^2)^{0.5}\big],$
 
- $p_{1} = \sum_{l\hspace{0.05cm}=\hspace{0.05cm}2}^{2^k} W_{l} · {\rm Q}\big[(l/\sigma^2)^{0.5}\big],$
 
+ $p_{1} = \sum_{i\hspace{0.05cm}=\hspace{0.05cm}1}^{n} W_{i} · {\rm Q}\big[(i/\sigma^2)^{0.5}\big].$
 
+ $p_{1} = \sum_{i\hspace{0.05cm}=\hspace{0.05cm}1}^{n} W_{i} · {\rm Q}\big[(i/\sigma^2)^{0.5}\big].$
  
{Specify the Union Bound for the&nbsp; $(8, 4, 4)$ code and various&nbsp; $\sigma$&nbsp;.
+
{Specify the Union Bound for the&nbsp; $(8, 4, 4)$&nbsp; code and various&nbsp; $\sigma$.
 
|type="{}"}
 
|type="{}"}
 
$\sigma = 1.0 \text{:} \hspace{0.4cm} p_{1} \ = \ $ { 32.15 3% } $\ \%$
 
$\sigma = 1.0 \text{:} \hspace{0.4cm} p_{1} \ = \ $ { 32.15 3% } $\ \%$
 
$\sigma = 0.5 \text{:} \hspace{0.4cm} p_{1} \ = \ $ { 0.0444 3% } $\ \%$
 
$\sigma = 0.5 \text{:} \hspace{0.4cm} p_{1} \ = \ $ { 0.0444 3% } $\ \%$
  
{Given the same boundary conditions, what does the ''Truncated Union Bound'' provide?
+
{Given the same boundary conditions, what does the&nbsp; "Truncated Union Bound"&nbsp; provide?
 
|type="{}"}
 
|type="{}"}
 
$\sigma = 1.0 \text{:} \hspace{0.4cm} p_{2} \ = \ $ { 31.92 3% } $\ \%$
 
$\sigma = 1.0 \text{:} \hspace{0.4cm} p_{2} \ = \ $ { 31.92 3% } $\ \%$
 
$\sigma = 0.5 \text{:} \hspace{0.4cm} p_{2} \ = \ $ { 0.044 3% } $\ \%$
 
$\sigma = 0.5 \text{:} \hspace{0.4cm} p_{2} \ = \ $ { 0.044 3% } $\ \%$
  
{Which statement is always true (for all constellations)?
+
{Which statement is always true&nbsp; (for all constellations)?
 
|type="[]"}
 
|type="[]"}
 
+ The block error probability is never greater than&nbsp; $p_{1}$.
 
+ The block error probability is never greater than&nbsp; $p_{1}$.
 
- The block error probability is never greater than&nbsp; $p_{2}$.
 
- The block error probability is never greater than&nbsp; $p_{2}$.
  
{How do you get from&nbsp; $p_{1}$&nbsp; to the Bhattacharyya bound&nbsp; $p_{3}$? By using
+
{How do you get from&nbsp; $p_{1}$&nbsp; to the&nbsp; "Bhattacharyya Bound"&nbsp; $p_{3}$?&nbsp;
 
|type="[]"}
 
|type="[]"}
+ replace the error function&nbsp; ${\rm Q}(x)$&nbsp; with the function&nbsp; ${\rm Q}_{\rm CR}(x)$&nbsp;,
+
+ Replace the error function&nbsp; ${\rm Q}(x)$&nbsp; with the function&nbsp; ${\rm Q}_{\rm CR}(x)$.
- sets the Bhattacharyya parameter&nbsp; $\beta = 1/\sigma$&nbsp; ,
+
- Set the Bhattacharyya parameter&nbsp; $\beta = 1/\sigma$.
+ instead of&nbsp; $\{W_i\}$&nbsp; uses the weight enumerator function&nbsp; $W(X)$&nbsp;.
+
+ Instead of&nbsp; $\{W_i\}$&nbsp; uses the weight enumerator function&nbsp; $W(X)$.
  
  
{Specify the Bhattacharyya bound for&nbsp; $\sigma = 1$&nbsp; and&nbsp; $\sigma = 0.5$&nbsp;.
+
{Specify the Bhattacharyya Bound for&nbsp; $\sigma = 1$&nbsp; and&nbsp; $\sigma = 0.5$&nbsp;.
 
|type="{}"}
 
|type="{}"}
 
$\sigma = 1.0 \text{:} \hspace{0.4cm} p_{3} \ = \ $ { 191.3 3% } $\ \%$
 
$\sigma = 1.0 \text{:} \hspace{0.4cm} p_{3} \ = \ $ { 191.3 3% } $\ \%$

Revision as of 15:37, 5 August 2022

Function  ${\rm Q}(x)$  and approximations;
it holds:  ${\rm Q_u}(x)\le{\rm Q}(x)\le{\rm Q_o}(x)$

We assume the following constellation:

  • A linear block code with code rate  $R = k/n$  and distance spectrum  $\{W_i\}, \ i = 1, \ \text{...} \ , n$,
  • an AWGN channel characterized by  $E_{\rm B}/N_{0}$   ⇒   convertible to noise power  $\sigma^2$,
  • a receiver based on  "soft decision"  as well as the  "maximum likelihood criterion".


Under the assumption valid for the entire exercise that always the zero-word  $\underline{x}_{1} = (0, 0, \text{... } \ , 0)$  is sent, the  "pairwise error probability"  with a different code word  $\underline{x}_{l} (l = 2,\ \text{...} \ , 2^k)$:

$$ {\rm Pr}[\hspace{0.05cm}\underline{x}_{\hspace{0.02cm}1} \hspace{-0.02cm}\mapsto \hspace{-0.02cm}\underline{x}_{\hspace{0.02cm}l}\hspace{0.05cm}] = {\rm Q}\left ( \sqrt{w_{\rm H}(\underline{x}_{\hspace{0.02cm}l})/\sigma^2} \right ) \hspace{0.05cm}.$$

The derivation of this relation can be found in  [Liv10].  Used in this equation are:

  • the  "Hamming weight"  $w_{\rm H}(\underline{x}_{l})$  of the code word  $\underline{x}_{l}$,


This allows various bounds to be specified for the block error probability:

$$p_1 = \sum_{l = 2}^{2^k}\hspace{0.05cm}{\rm Pr}[\hspace{0.05cm}\underline{x}_{\hspace{0.02cm}1} \hspace{-0.02cm}\mapsto \hspace{-0.02cm}\underline{x}_{\hspace{0.02cm}l}\hspace{0.05cm}] = \sum_{l \hspace{0.05cm}= \hspace{0.05cm}2}^{2^k}\hspace{0.05cm}{\rm Q}\left ( \sqrt{w_{\rm H}(\underline{x}_{\hspace{0.02cm}l})/\sigma^2} \right ) \hspace{0.05cm},$$
$$p_2 = W_{d_{\rm min}} \cdot {\rm Q}\left ( \sqrt{d_{\rm min}/\sigma^2} \right ) \hspace{0.05cm},$$
$$p_3 = W(\beta) - 1\hspace{0.05cm},\hspace{0.2cm} {\rm with}\hspace{0.15cm} \beta = {\rm e}^{ - 1/(2\sigma^2) } \hspace{0.05cm}.$$
In this case,  replace the distance spectrum  $\{W_i\}$  with the weight enumerator function:
$$\left \{ \hspace{0.05cm} W_i \hspace{0.05cm} \right \} \hspace{0.3cm} \Leftrightarrow \hspace{0.3cm} W(X) = \sum_{i=0 }^{n} W_i \cdot X^{i} = W_0 + W_1 \cdot X + W_2 \cdot X^{2} + ... \hspace{0.05cm} + W_n \cdot X^{n}\hspace{0.05cm}.$$

In the transition from the  "Union Bound"  $p_{1}$  to the more imprecise bound  $p_{3}$  among others

  • Both functions are shown in the above graph  (red and green curve, resp.).


In the  "Exercise 1.16Z"  the relationship between these functions is evaluated numerically and referenced to the bounds  ${\rm Q}_{\rm o}(x)$ and ${\rm Q}_{\rm u}(x)$  which are also drawn in the above graph.



Hints:

  • The above cited reference  "[Liv10]"  refers to the lecture manuscript "Liva, G.:  Channel Coding.  Chair of Communications Engineering, TU Munich and DLR Oberpfaffenhofen, 2010."



Questions

1

Which equation applies to the  "Union Bound"?

$p_{1} = \sum_{l\hspace{0.05cm}=\hspace{0.05cm}2}^{2^k} W_{l} · {\rm Q}\big[(l/\sigma^2)^{0.5}\big],$
$p_{1} = \sum_{i\hspace{0.05cm}=\hspace{0.05cm}1}^{n} W_{i} · {\rm Q}\big[(i/\sigma^2)^{0.5}\big].$

2

Specify the Union Bound for the  $(8, 4, 4)$  code and various  $\sigma$.

$\sigma = 1.0 \text{:} \hspace{0.4cm} p_{1} \ = \ $

$\ \%$
$\sigma = 0.5 \text{:} \hspace{0.4cm} p_{1} \ = \ $

$\ \%$

3

Given the same boundary conditions, what does the  "Truncated Union Bound"  provide?

$\sigma = 1.0 \text{:} \hspace{0.4cm} p_{2} \ = \ $

$\ \%$
$\sigma = 0.5 \text{:} \hspace{0.4cm} p_{2} \ = \ $

$\ \%$

4

Which statement is always true  (for all constellations)?

The block error probability is never greater than  $p_{1}$.
The block error probability is never greater than  $p_{2}$.

5

How do you get from  $p_{1}$  to the  "Bhattacharyya Bound"  $p_{3}$? 

Replace the error function  ${\rm Q}(x)$  with the function  ${\rm Q}_{\rm CR}(x)$.
Set the Bhattacharyya parameter  $\beta = 1/\sigma$.
Instead of  $\{W_i\}$  uses the weight enumerator function  $W(X)$.

6

Specify the Bhattacharyya Bound for  $\sigma = 1$  and  $\sigma = 0.5$ .

$\sigma = 1.0 \text{:} \hspace{0.4cm} p_{3} \ = \ $

$\ \%$
$\sigma = 0.5 \text{:} \hspace{0.4cm} p_{3} \ = \ $

$\ \%$


Solution

(1)  Richtig ist die Antwort 2. Das Distanzspektrum $\{W_i\}$ ist definiert für $i = 0, \ \text{...} \ , \ n$:

  • $W_{1}$ indicates how often the Hamming weight $w_{\rm H}(\underline{x}_{i}) = 1$ occurs.
  • $W_{n}$ indicates how often the Hamming weight $w_{\rm H}(\underline{x}_{i}) = n$ occurs.


With that, the Union Bound is:

$$p_1 = {\rm Pr(Union \hspace{0.15cm}Bound)}= \sum_{i = 1}^{n}\hspace{0.05cm}W_i \cdot {\rm Q}\left ( \sqrt{i/\sigma^2} \right ) \hspace{0.05cm}.$$


(2)  The distance spectrum of the $(8, 4, 4)$ code was given as $W_{0} = 1 , \ W_{4} = 14, \ W_{8} = 1$. Thus, one obtains for $\sigma = 1$:

$$p_1 = W_4 \cdot {\rm Q}\left ( 2 \right ) + W_8 \cdot {\rm Q}\left ( 2 \cdot \sqrt{2} \right ) = 14 \cdot 2.28 \cdot 10^{-2}+ 1 \cdot 0.23 \cdot 10^{-2} \hspace{0.15cm}\underline{\approx 32.15\%}\hspace{0.05cm},$$

or for $\sigma = 0.5$:

$$p_1 = 14 \cdot {\rm Q}\left ( 4 \right ) + {\rm Q}\left ( 4 \cdot \sqrt{2} \right ) = 14 \cdot 3.17 \cdot 10^{-5}+ 1.1 \cdot 10^{-8} \hspace{0.15cm}\underline{\approx 0.0444 \%}\hspace{0.05cm}.$$


(3)  With the minimum distance $d_{\rm min} = 4$ we get:

$$\sigma = 1.0\text{:} \hspace{0.4cm} p_2 \hspace{-0.15cm}\ = \ \hspace{-0.15cm} W_4 \cdot {\rm Q}\left ( 2 \right ) \hspace{0.15cm}\underline{= 31.92\%}\hspace{0.05cm},$$
$$\sigma = 0.5\text{:} \hspace{0.4cm} p_2 \hspace{-0.15cm}\ = \ \hspace{-0.15cm}W_4 \cdot {\rm Q}\left ( 4 \right ) \approx p_1 \hspace{0.15cm}\underline{ = 0.0444 \%}\hspace{0.05cm}.$$


(4)  The correct solution is suggestion 1:

  • The Union Bound - denoted here by $p_{1}$ - is an upper bound on the block error probability in all cases.
  • For the bound $p_{2}$ (Truncated Union Bound) this is not always true.
  • For example, in the $(7, 4, 3)$ Hamming code   ⇒   $W_{3} = W_{4} = 7, \ W_{7} = 1$ is obtained with standard deviation $\sigma = 1$:
$$p_2 \hspace{-0.15cm}\ = \ \hspace{-0.15cm} 7 \cdot {\rm Q}\left ( \sqrt{3} \right ) = 7 \cdot 4.18 \cdot 10^{-2} \approx 0.293\hspace{0.05cm},$$
$$p_1 \hspace{-0.15cm}\ = \ \hspace{-0.15cm} p_2 + 7 \cdot {\rm Q}\left ( \sqrt{4} \right )+ 1 \cdot {\rm Q}\left ( \sqrt{7} \right ) \approx 0.455 \hspace{0.05cm}.$$

The actual block error probability is likely to be between $p_{2} = 29.3\%$ and $p_{1} = 45.5\%$ (but has not been verified).
That is,   $p_{2}$ is not an upper bound.


(5)  Correct are suggested solutions 1 and 3, as the following calculation for the $(8, 4, 4)$ code shows:

  • It holds ${\rm Q}(x) ≤ {\rm Q_{CR}}(x) = {\rm e}^{-x^2/2}$. Thus, for the Union Bound
$$p_1 = W_4 \cdot {\rm Q}\left ( \sqrt{4/\sigma^2} \right ) +W_8 \cdot {\rm Q}\left ( \sqrt{8/\sigma^2} \right )$$
another upper bound can be specified:
$$p_1 \le W_4 \cdot {\rm e}^{ - {4}/(2 \sigma^2) } +W_8 \cdot {\rm e}^{ - {8}/(2 \sigma^2) } \hspace{0.05cm}.$$
  • With $\beta = {\rm e}^{-1/(2\sigma^2)}$ can be written for this also (so the given $\beta = 1/\sigma$ is wrong):
$$p_1 \le W_4 \cdot \beta^4 + W_8 \cdot \beta^8 \hspace{0.05cm}.$$
  • The weight function of the $(8, 4, 4)$ code is:
$$W(X) = 1 + W_4 \cdot X^4 + W_8 \cdot X^8 \hspace{0.3cm} \Rightarrow \hspace{0.3cm} W(\beta) - 1 = W_4 \cdot \beta^4 + W_8 \cdot \beta^8\hspace{0.3cm} \Rightarrow \hspace{0.3cm} p_3 = W(\beta) - 1 \ge p_1\hspace{0.05cm}.$$


(6)  With $\sigma = 1$, the Bhattacharyya parameter is $\beta = {\rm e}^{-0.5} = 0.6065$, and thus one obtains for the Bhattacharyya bound:

$$p_3 = 14 \cdot \beta^4 + \beta^8 = 14 \cdot 0.135 + 0.018= 1.913 \hspace{0.15cm}\underline{= 191.3%}\hspace{0.05cm}.$$
  • Considering that $p_{3}$ is a bound for a probability, $p_{3} = 1.913$ is only a trivial bound.
  • For $\sigma = 0.5$, on the other hand, $\beta = {\rm e}^{-2} \approx 0.135.$ Then holds:
$$p_3 = 14 \cdot \beta^4 + \beta^8 = 14 \cdot 3.35 \cdot 10^{-4} + 1.1 \cdot 10^{-7} \hspace{0.15cm}\underline{= 0.47 \%}\hspace{0.05cm}.$$

A comparison with subtask (2) shows that in the present example the Bhattacharyya bound $p_{3}$ is above the union bound $p_{1}$ by a factor $(0.47 - 10^{-2})/(0.044 - 10^{-2}) > 10$.

  • The reason for this large deviation is the Chernoff-Rubin bound, which is well above the ${\rm Q}$ function.
  • In "Exercise 1.16Z", the deviation between ${\rm Q}_{\rm CR}$ and ${\rm Q}(x)$ is also calculated quantitatively:
$${{\rm Q_{CR}}( x )}/{{\rm Q}( x )} \approx 2.5 \cdot x \hspace{0.3cm} \Rightarrow \hspace{0.3cm} {{\rm Q_{CR}}( x = 4 )}/{{\rm Q}( x = 4)} \approx 10 \hspace{0.05cm}.$$