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

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The derivation of this relation can be found in [Liv10]. Used in this equation are:
 
The derivation of this relation can be found in [Liv10]. Used in this equation are:
*the  [[Theory_of_Stochastic_Signals/Gaussian_Distributed_Random_Variables#Exceedance_probability|complementary Gaussian error function]]  ${\rm Q}(x)$,
+
*the  [[Theory_of_Stochastic_Signals/Gaussian_Distributed_Random_Variables#Exceedance_probability|"complementary Gaussian error function"]]  ${\rm Q}(x)$,
*the  [[Channel_Coding/Objective_of_Channel_Coding#Important_definitions_for_block_coding|Hamming weight]]  $w_{\rm H}(\underline{x}_{l})$  of the codeword  $\underline{x}_{l}$,
+
*the  [[Channel_Coding/Objective_of_Channel_Coding#Important_definitions_for_block_coding|"Hamming weight"]]  $w_{\rm H}(\underline{x}_{l})$  of the codeword  $\underline{x}_{l}$,
*the  [[Digital_Signal_Transmission/Optimization_of_Baseband_Transmission_Systems#System_optimization_with_power_limitation|AWGN noise power]]  $\sigma^2 = (2 - R - E_{\rm B}/N_{0})^{-1}.$  
+
*the  [[Digital_Signal_Transmission/Optimization_of_Baseband_Transmission_Systems#System_optimization_with_power_limitation|"AWGN noise power"]]  $\sigma^2 = (2 - R - E_{\rm B}/N_{0})^{-1}.$  
  
  
 
Damit lassen sich verschiedene Schranken für die Blockfehlerwahrscheinlichkeit angeben:
 
Damit lassen sich verschiedene Schranken für die Blockfehlerwahrscheinlichkeit angeben:
  
*the so called  [[Channel_Coding/Limits_for_Block_Error_Probability#Union_Bound_of_the_block_error_probability|Union Bound]]  (UB):
+
*the so called  [[Channel_Coding/Limits_for_Block_Error_Probability#Union_Bound_of_the_block_error_probability|"Union Bound"]]  (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  [[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]]  (TUB):
+
*the so called  [[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"]]  (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  [[Channel_Coding/Limits_for_Block_Error_Probability#The_upper_bound_according_to_Bhattacharyya|Bhattacharyya bound]]:
+
*the  [[Channel_Coding/Limits_for_Block_Error_Probability#The_upper_bound_according_to_Bhattacharyya|"Bhattacharyya bound"]]:
 
   
 
   
 
:$$p_3 = W(\beta) - 1\hspace{0.05cm},\hspace{0.2cm} {\rm mit}\hspace{0.15cm} \beta = {\rm e}^{ - 1/(2\sigma^2) } \hspace{0.05cm}.$$
 
:$$p_3 = W(\beta) - 1\hspace{0.05cm},\hspace{0.2cm} {\rm mit}\hspace{0.15cm} \beta = {\rm e}^{ - 1/(2\sigma^2) } \hspace{0.05cm}.$$
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In the transition from the ''Union Bound''  $p_{1}$  to the more imprecise bound  $p_{3}$  among others the function  ${\rm Q}(x)$  is replaced by the  [https://en.wikipedia.org/wiki/Chernoff_bound Chernoff-Rubin bound]  ${\rm Q}_{\rm CR}(x)$ . Both functions are shown in the above graph (red and green curve, respectively).
 
In the transition from the ''Union Bound''  $p_{1}$  to the more imprecise bound  $p_{3}$  among others the function  ${\rm Q}(x)$  is replaced by the  [https://en.wikipedia.org/wiki/Chernoff_bound Chernoff-Rubin bound]  ${\rm Q}_{\rm CR}(x)$ . Both functions are shown in the above graph (red and green curve, respectively).
  
In the  [[Aufgaben:Exercise_1.16Z:_Bounds_for_the_Gaussian_Error_Function|Exercise 1.16Z]]  the relationship between these functions is evaluated numerically and referenced to the bounds  ${\rm Q}_{o}(x)$ and ${\rm Q}_{u}(x)$  which are also drawn in the above graph.
+
In the  [[Aufgaben:Exercise_1.16Z:_Bounds_for_the_Gaussian_Error_Function|"Exercise 1.16Z"]]  the relationship between these functions is evaluated numerically and referenced to the bounds  ${\rm Q}_{o}(x)$ and ${\rm Q}_{u}(x)$  which are also drawn in the above graph.
  
  
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Hints:  
 
Hints:  
* This exercise belongs to the chapter  [[Channel_Coding/Schranken_für_die_Blockfehlerwahrscheinlichkeit|Schranken für die Blockfehlerwahrscheinlichkeit]].
+
* This exercise belongs to the chapter  [[Channel_Coding/Schranken_für_die_Blockfehlerwahrscheinlichkeit|"Block error probability bounds"]].
* Die oben zitierte Literaturstelle  [Liv10] verweist auf das Vorlesungsmanuskript "Liva, G.: ''Channel Coding''.  Lehrstuhl für Nachrichtentechnik, TU München und DLR Oberpfaffenhofen, 2010."
+
* The above cited reference [Liv10] refers to the lecture manuscript "Liva, G.: ''Channel Coding''.  Chair of Communications Engineering, TU Munich and DLR Oberpfaffenhofen, 2010."
* Weiter verweisen wir auf das interaktive Applet  [[Applets:Komplementäre_Gaußsche_Fehlerfunktionen| Komplementäre Gaußsche Fehlerfunktionen]].
+
* Further we refer to the interactive applet  [[Applets:Komplementäre_Gaußsche_Fehlerfunktionen| "Complementary Gaussian error functions"]].
  
  
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===Fragebogen===
+
===Questions===
  
 
<quiz display=simple>
 
<quiz display=simple>
{Welche Gleichung gilt für die ''Union Bound''?
+
{Which equation applies to the ''Union Bound''?
 
|type="[]"}
 
|type="[]"}
 
- $p_{1} = \sum_{l\hspace{0.05cm}=\hspace{0.05cm}2}^{2^k} W_{l} · {\rm Q}\big[(l/\sigma^2)^{0.5}\big],$
 
- $p_{1} = \sum_{l\hspace{0.05cm}=\hspace{0.05cm}2}^{2^k} W_{l} · {\rm Q}\big[(l/\sigma^2)^{0.5}\big],$
 
+ $p_{1} = \sum_{i\hspace{0.05cm}=\hspace{0.05cm}1}^{n} W_{i} · {\rm Q}\big[(i/\sigma^2)^{0.5}\big].$
 
+ $p_{1} = \sum_{i\hspace{0.05cm}=\hspace{0.05cm}1}^{n} W_{i} · {\rm Q}\big[(i/\sigma^2)^{0.5}\big].$
  
{Geben Sie die Union Bound für den&nbsp; $(8, 4, 4)$–Code und verschiedene&nbsp; $\sigma$&nbsp; an.
+
{Specify the Union Bound for the&nbsp; $(8, 4, 4)$ code and various&nbsp; $\sigma$&nbsp;.
 
|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% } $\ \%$
  
{Was liefert die ''Truncated Union Bound'' bei gleichen Randbedingungen?
+
{Given the same boundary conditions, what does the ''Truncated Union Bound'' 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% } $\ \%$
  
{Welche Aussage gilt immer (für alle Konstellationen)?
+
{Which statement is always true (for all constellations)?
 
|type="[]"}
 
|type="[]"}
+ Die Blockfehlerwahrscheinlichkeit ist nie größer als&nbsp; $p_{1}$.
+
+ The block error probability is never greater than&nbsp; $p_{1}$.
- Die Blockfehlerwahrscheinlichkeit ist nie größer als&nbsp; $p_{2}$.
+
- The block error probability is never greater than&nbsp; $p_{2}$.
  
{Wie kommt man von&nbsp; $p_{1}$&nbsp; zur Bhattacharyya–Schranke&nbsp; $p_{3}$? Dadurch, dass man
+
{How do you get from&nbsp; $p_{1}$&nbsp; to the Bhattacharyya bound&nbsp; $p_{3}$? By using
 
|type="[]"}
 
|type="[]"}
+ die Fehlerfunktion&nbsp; ${\rm Q}(x)$&nbsp; durch die Funktion&nbsp; ${\rm Q}_{\rm CR}(x)$&nbsp; ersetzt,
+
+ replace the error function&nbsp; ${\rm Q}(x)$&nbsp; with the function&nbsp; ${\rm Q}_{\rm CR}(x)$&nbsp;,
- den Bhattacharyya–Parameter&nbsp; $\beta = 1/\sigma$&nbsp; setzt,
+
- sets the Bhattacharyya parameter&nbsp; $\beta = 1/\sigma$&nbsp; ,
+ statt&nbsp; $\{W_i\}$&nbsp; die Gewichtsfunktion&nbsp; $W(X)$&nbsp; verwendet.
+
+ instead of&nbsp; $\{W_i\}$&nbsp; uses the weight enumerator function&nbsp; $W(X)$&nbsp;.
  
  
{Geben Sie die Bhattacharyya–Schranke für&nbsp; $\sigma = 1$&nbsp; und&nbsp; $\sigma = 0.5$&nbsp; an.
+
{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% } $\ \%$
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</quiz>
 
</quiz>
  
===Musterlösung===
+
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
 
'''(1)'''&nbsp; Richtig ist die  <u>Antwort 2</u>. Das Distanzspektrum $\{W_i\}$ ist definiert für $i = 0, \ \text{...} \ , \ n$:
 
'''(1)'''&nbsp; Richtig ist die  <u>Antwort 2</u>. Das Distanzspektrum $\{W_i\}$ ist definiert für $i = 0, \ \text{...} \ , \ n$:
  
*$W_{1}$ gibt an, wie oft das Hamming–Gewicht $w_{\rm H}(\underline{x}_{i}) = 1$ auftritt.
+
*$W_{1}$ indicates how often the Hamming weight $w_{\rm H}(\underline{x}_{i}) = 1$ occurs.
*$W_{n}$ gibt an, wie oft das Hamming–Gewicht $w_{\rm H}(\underline{x}_{i}) = n$ auftritt.
+
*$W_{n}$ indicates how often the Hamming weight $w_{\rm H}(\underline{x}_{i}) = n$ occurs.
  
  
Damit lautet die ''Union Bound'':
+
With that, the ''Union Bound'' is:
  
 
:$$p_1 = {\rm Pr(Union \hspace{0.15cm}Bound)}= \sum_{i = 1}^{n}\hspace{0.05cm}W_i \cdot {\rm Q}\left ( \sqrt{i/\sigma^2} \right ) \hspace{0.05cm}.$$
 
:$$p_1 = {\rm Pr(Union \hspace{0.15cm}Bound)}= \sum_{i = 1}^{n}\hspace{0.05cm}W_i \cdot {\rm Q}\left ( \sqrt{i/\sigma^2} \right ) \hspace{0.05cm}.$$
 
   
 
   
  
'''(2)'''&nbsp; Das Distanzspektrum des $(8, 4, 4)$–Codes wurde mit $W_{0} = 1 , \ W_{4} = 14, \ W_{8} = 1$ angegeben. Somit erhält man für $\sigma = 1$:
+
'''(2)'''&nbsp; 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 )
 
:$$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},$$
 
= 14 \cdot 2.28 \cdot 10^{-2}+ 1 \cdot 0.23 \cdot 10^{-2} \hspace{0.15cm}\underline{\approx 32.15\%}\hspace{0.05cm},$$
  
bzw. für $\sigma = 0.5$:
+
or for $\sigma = 0.5$:
 
:$$p_1 =  14 \cdot {\rm Q}\left ( 4 \right ) + {\rm Q}\left ( 4 \cdot \sqrt{2} \right )
 
:$$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}.$$
 
= 14 \cdot 3.17 \cdot 10^{-5}+ 1.1 \cdot 10^{-8} \hspace{0.15cm}\underline{\approx 0.0444 \%}\hspace{0.05cm}.$$
 
   
 
   
  
'''(3)'''&nbsp; Mit der Minimaldistanz $d_{\rm min} = 4$ erhält man:
+
'''(3)'''&nbsp; With the minimum distance $d_{\rm min} = 4$ we get:
 
   
 
   
 
:$$\sigma = 1.0\text{:} \hspace{0.4cm} p_2 \hspace{-0.15cm}\ = \ \hspace{-0.15cm} W_4 \cdot {\rm Q}\left ( 2 \right ) \hspace{0.15cm}\underline{= 31.92\%}\hspace{0.05cm},$$
 
:$$\sigma = 1.0\text{:} \hspace{0.4cm} p_2 \hspace{-0.15cm}\ = \ \hspace{-0.15cm} W_4 \cdot {\rm Q}\left ( 2 \right ) \hspace{0.15cm}\underline{= 31.92\%}\hspace{0.05cm},$$
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'''(4)'''&nbsp; Richtig ist der <u>Lösungsvorschlag 1</u>:  
+
'''(4)'''&nbsp; The correct solution is <u>suggestion 1</u>:  
*Die ''Union Bound'' – hier mit $p_{1}$ bezeichnet – ist in jedem Fall eine obere Schranke für die Blockfehlerwahrscheinlichkeit.  
+
*The ''Union Bound'' - denoted here by $p_{1}$ - is an upper bound on the block error probability in all cases.  
*Für die Schranke $p_{2}$ (''Truncated Union Bound'') trifft das nicht immer zu.  
+
*For the bound $p_{2}$ (''Truncated Union Bound'') this is not always true.  
*Beispielsweise erhält man beim $(7, 4, 3)$–Hamming–Code  &nbsp; ⇒ &nbsp; $W_{3} = W_{4} = 7, \ W_{7} = 1$ mit der Streuung $\sigma = 1$:
+
*For example, in the $(7, 4, 3)$ Hamming code &nbsp; ⇒ &nbsp; $W_{3} = W_{4} = 7, \ W_{7} = 1$ is obtained with standard deviation $\sigma = 1$:
 
   
 
   
 
:$$p_2 \hspace{-0.15cm}\ = \ \hspace{-0.15cm} 7 \cdot {\rm Q}\left ( \sqrt{3} \right ) = 7 \cdot 4.18 \cdot 10^{-2} \approx 0.293\hspace{0.05cm},$$
 
:$$p_2 \hspace{-0.15cm}\ = \ \hspace{-0.15cm} 7 \cdot {\rm Q}\left ( \sqrt{3} \right ) = 7 \cdot 4.18 \cdot 10^{-2} \approx 0.293\hspace{0.05cm},$$
 
:$$p_1 \hspace{-0.15cm}\ = \ \hspace{-0.15cm} p_2 + 7 \cdot {\rm Q}\left ( \sqrt{4} \right )+ 1 \cdot {\rm Q}\left ( \sqrt{7} \right ) \approx 0.455 \hspace{0.05cm}.$$
 
:$$p_1 \hspace{-0.15cm}\ = \ \hspace{-0.15cm} p_2 + 7 \cdot {\rm Q}\left ( \sqrt{4} \right )+ 1 \cdot {\rm Q}\left ( \sqrt{7} \right ) \approx 0.455 \hspace{0.05cm}.$$
  
Die tatsächliche Blockfehlerwahrscheinlichkeit wird wahrscheinlich zwischen $p_{2} = 29.3\%$ und $p_{1} = 45.5\%$ liegen (wurde allerdings nicht nachgeprüft). <br>Das heißt: &nbsp; $p_{2}$ ist keine obere Schranke.
+
The actual block error probability is likely to be between $p_{2} = 29.3\%$ and $p_{1} = 45.5\%$ (but has not been verified). <br>That is, &nbsp; $p_{2}$ is not an upper bound.
  
  
'''(5)'''&nbsp; Richtig sind die <u>Lösungsvorschläge 1 und 3</u>, wie die folgende Rechnung für den $(8, 4, 4)$–Code zeigt:
+
'''(5)'''&nbsp; Correct are <u>suggested solutions 1 and 3</u>, as the following calculation for the $(8, 4, 4)$ code shows:
  
*Es gilt ${\rm Q}(x) ≤ {\rm Q_{CR}}(x) = {\rm e}^{-x^2/2}$. Damit kann für die Union Bound
+
*It holds ${\rm Q}(x) ≤ {\rm Q_{CR}}(x) = {\rm e}^{-x^2/2}$. Thus, for the Union Bound
 
   
 
   
 
:$$p_1 = W_4 \cdot {\rm Q}\left ( \sqrt{4/\sigma^2} \right ) +W_8 \cdot {\rm Q}\left ( \sqrt{8/\sigma^2} \right )$$
 
:$$p_1 = W_4 \cdot {\rm Q}\left ( \sqrt{4/\sigma^2} \right ) +W_8 \cdot {\rm Q}\left ( \sqrt{8/\sigma^2} \right )$$
  
:eine weitere obere Schranke angegeben werden:
+
:another upper bound can be specified:
 
   
 
   
 
:$$p_1 \le W_4 \cdot {\rm e}^{ - {4}/(2 \sigma^2) } +W_8 \cdot {\rm e}^{ - {8}/(2 \sigma^2) } \hspace{0.05cm}.$$
 
:$$p_1 \le W_4 \cdot {\rm e}^{ - {4}/(2 \sigma^2) } +W_8 \cdot {\rm e}^{ - {8}/(2 \sigma^2) } \hspace{0.05cm}.$$
  
*Mit $\beta = {\rm e}^{–1/(2\sigma^2)}$ kann hierfür auch geschrieben werden (das vorgegebene $\beta = 1/\sigma$ ist also falsch):
+
*With $\beta = {\rm e}^{-1/(2\sigma^2)}$ can be written for this also (so the given $\beta = 1/\sigma$ is wrong):
 
   
 
   
 
:$$p_1 \le W_4 \cdot \beta^4 + W_8 \cdot \beta^8 \hspace{0.05cm}.$$
 
:$$p_1 \le W_4 \cdot \beta^4 + W_8 \cdot \beta^8 \hspace{0.05cm}.$$
  
*Die Gewichtsfunktion des $(8, 4, 4)$–Codes lautet:
+
*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}
 
:$$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}
Line 148: Line 148:
  
  
'''(6)'''&nbsp; Mit $\sigma = 1$ lautet der Bhattacharyya–Parameter $\beta = {\rm e}^{–0.5} = 0.6065$ und man erhält damit für die Bhattacharyya–Schranke:
+
'''(6)'''&nbsp; With $\sigma = 1$, the Bhattacharyya parameter is $\beta = {\rm e}^{-0.5} = 0.6065$, and thus one obtains for the Bhattacharyya bound:
 
   
 
   
 
:$$p_3 = 14 \cdot \beta^4 + \beta^8 = 14 \cdot 0.135 + 0.018= 1.913 \hspace{0.15cm}\underline{= 191.3%}\hspace{0.05cm}.$$
 
:$$p_3 = 14 \cdot \beta^4 + \beta^8 = 14 \cdot 0.135 + 0.018= 1.913 \hspace{0.15cm}\underline{= 191.3%}\hspace{0.05cm}.$$
  
*Berücksichtigt man, dass $p_{3}$ (eine Schranke für) eine Wahrscheinlichkeit angibt, so ist $p_{3} = 1.913$ nur eine triviale Schranke.  
+
*Considering that $p_{3}$ is a bound for a probability, $p_{3} = 1.913$ is only a trivial bound.  
*Für $\sigma = 0.5$ ergibt sich dagegen $\beta = {\rm e}^{–2}  \approx 0.135.$ Dann gilt:
+
*For $\sigma = 0.5$, on the other hand, $\beta = {\rm e}^{-2}  \approx 0.135.$ Then holds:
 
   
 
   
 
:$$p_3 = 14 \cdot \beta^4 + \beta^8 = 14 \cdot 3.35 \cdot 10^{-4} + 1.1 \cdot 10^{-7} \hspace{0.15cm}\underline{= 0.47 \%}\hspace{0.05cm}.$$
 
:$$p_3 = 14 \cdot \beta^4 + \beta^8 = 14 \cdot 3.35 \cdot 10^{-4} + 1.1 \cdot 10^{-7} \hspace{0.15cm}\underline{= 0.47 \%}\hspace{0.05cm}.$$
  
Ein Vergleich mit der Teilaufgabe (2) zeigt, dass im vorliegenden Beispiel die Bhattacharyya–Schranke $p_{3}$ um den Faktor $(0.47 · 10^{–2})/(0.044 · 10^{–2}) > 10$ oberhalb der ''Union Bound'' $p_{1}$ liegt.  
+
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 $(0.47 - 10^{-2})/(0.044 - 10^{-2}) > 10$.  
*Der Grund für diese große Abweichung ist die Chernoff–Rubin–Schranke, die deutlich oberhalb der ${\rm Q}$–Funktion liegt.  
+
*The reason for this large deviation is the Chernoff-Rubin bound, which is well above the ${\rm Q}$ function.  
*In der [[Aufgaben:Aufgabe_1.16Z:_Schranken_für_die_Gaußsche_Fehlerfunktion|Aufgabe 1.16Z]] wird die Abweichung zwischen ${\rm Q}_{\rm CR}$ und ${\rm Q}(x)$ auch quantitativ berechnet:
+
*In [[Aufgaben:Exercise_1.16Z:_Bounds_for_the_Gaussian_Error_Function|"Exercise 1.16Z"]], the deviation between ${\rm Q}_{\rm CR}$ and ${\rm Q}(x)$ is also calculated quantitatively:
 
   
 
   
 
:$${{\rm Q_{CR}}( x )}/{{\rm Q}( x )} \approx 2.5 \cdot x \hspace{0.3cm} \Rightarrow \hspace{0.3cm} {{\rm Q_{CR}}( x = 4 )}/{{\rm Q}( x = 4)} \approx 10 \hspace{0.05cm}.$$
 
:$${{\rm Q_{CR}}( x )}/{{\rm Q}( x )} \approx 2.5 \cdot x \hspace{0.3cm} \Rightarrow \hspace{0.3cm} {{\rm Q_{CR}}( x = 4 )}/{{\rm Q}( x = 4)} \approx 10 \hspace{0.05cm}.$$

Revision as of 18:33, 30 July 2022

Error function  ${\rm Q}(x)$  and approximations

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 null word  $\underline{x}_{1} = (0, 0, \text{... } \ , 0)$  is sent, the  "pairwise error probability" with a different codeword  $\underline{x}_{l} (l = 2,\ \text{...} \ , 2^k)$:

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

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


Damit lassen sich verschiedene Schranken für die Blockfehlerwahrscheinlichkeit angeben:

$$p_1 = \sum_{l = 2}^{2^k}\hspace{0.05cm}{\rm Pr}[\hspace{0.05cm}\underline{x}_{\hspace{0.02cm}1} \hspace{-0.02cm}\mapsto \hspace{-0.02cm}\underline{x}_{\hspace{0.02cm}l}\hspace{0.05cm}] = \sum_{l \hspace{0.05cm}= \hspace{0.05cm}2}^{2^k}\hspace{0.05cm}{\rm Q}\left ( \sqrt{w_{\rm H}(\underline{x}_{\hspace{0.02cm}l})/\sigma^2} \right ) \hspace{0.05cm},$$
$$p_2 = W_{d_{\rm min}} \cdot {\rm Q}\left ( \sqrt{d_{\rm min}/\sigma^2} \right ) \hspace{0.05cm},$$
$$p_3 = W(\beta) - 1\hspace{0.05cm},\hspace{0.2cm} {\rm mit}\hspace{0.15cm} \beta = {\rm e}^{ - 1/(2\sigma^2) } \hspace{0.05cm}.$$
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 the function  ${\rm Q}(x)$  is replaced by the  Chernoff-Rubin bound  ${\rm Q}_{\rm CR}(x)$ . Both functions are shown in the above graph (red and green curve, respectively).

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



Hints:



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  $p_{3}$? By using

replace the error function  ${\rm Q}(x)$  with the function  ${\rm Q}_{\rm CR}(x)$ ,
sets 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:
$${{\rm Q_{CR}}( x )}/{{\rm Q}( x )} \approx 2.5 \cdot x \hspace{0.3cm} \Rightarrow \hspace{0.3cm} {{\rm Q_{CR}}( x = 4 )}/{{\rm Q}( x = 4)} \approx 10 \hspace{0.05cm}.$$