Difference between revisions of "Aufgaben:Exercise 4.4: Extrinsic L-values at SPC"

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:$$\underline{x}^{(-i)} = \big ( \hspace{0.03cm}x_1, \hspace{0.05cm} \text{...} \hspace{0.05cm} , \hspace{0.03cm} x_{i-1}, \hspace{0.43cm} x_{i+1},  \hspace{0.05cm} \text{...} \hspace{0.05cm} , x_{n} \hspace{0.03cm} \big )\hspace{0.03cm}. $$
 
:$$\underline{x}^{(-i)} = \big ( \hspace{0.03cm}x_1, \hspace{0.05cm} \text{...} \hspace{0.05cm} , \hspace{0.03cm} x_{i-1}, \hspace{0.43cm} x_{i+1},  \hspace{0.05cm} \text{...} \hspace{0.05cm} , x_{n} \hspace{0.03cm} \big )\hspace{0.03cm}. $$
  
Der extrinsische  $L$–Wert über das  $i$–te Codesymbol lautet mit dem  [[Channel_Coding/Objective_of_Channel_Coding#Important_definitions_for_block_coding|"Hamming–Gewicht"]]  $w_{\rm H}$  der verkürzten Folge  $\underline{x}^{(-i)}$:
+
The extrinsic  $L$ value over the  $i$th code symbol reads with the  [[Channel_Coding/Objective_of_Channel_Coding#Important_definitions_for_block_coding|"Hamming–weight"]]  $w_{\rm H}$  of the truncated sequence  $\underline{x}^{(-i)}$:
 
:$$L_{\rm E}(i) = \frac{{\rm Pr} \left [w_{\rm H}(\underline{x}^{(-i)})\hspace{0.15cm}{\rm ist \hspace{0.15cm} gerade} \hspace{0.05cm} | \hspace{0.05cm}\underline{y} \hspace{0.05cm}\right ]}{{\rm Pr} \left [w_{\rm H}(\underline{x}^{(-i)})\hspace{0.15cm}{\rm ist \hspace{0.15cm} ungerade} \hspace{0.05cm} | \hspace{0.05cm}\underline{y} \hspace{0.05cm}\right ]}
 
:$$L_{\rm E}(i) = \frac{{\rm Pr} \left [w_{\rm H}(\underline{x}^{(-i)})\hspace{0.15cm}{\rm ist \hspace{0.15cm} gerade} \hspace{0.05cm} | \hspace{0.05cm}\underline{y} \hspace{0.05cm}\right ]}{{\rm Pr} \left [w_{\rm H}(\underline{x}^{(-i)})\hspace{0.15cm}{\rm ist \hspace{0.15cm} ungerade} \hspace{0.05cm} | \hspace{0.05cm}\underline{y} \hspace{0.05cm}\right ]}
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
*Ist die Wahrscheinlichkeit im Zähler größer als die im Nenner, so ist  $L_{\rm E}(i) > 0$  und damit wird auch der Aposteriori–$L$–Wert  $L_{\rm APP}(i) = L_{\rm A}(i) + L_{\rm E}(i)$  vergrößert, das heißt tendenziell in Richtung des Symbols  $x_i = 0$  beeinflusst.  
+
*If the probability in the numerator is greater than that in the denominator, then  $L_{\rm E}(i) > 0$  and thus the a posteriori–$L$– value  $L_{\rm APP}(i) = L_{\rm A}(i) + L_{\rm E}(i)$  magnified, that is tends to be affected in the direction of the symbol  $x_i = 0$ .  
*Bei&nbsp; $L_{\rm E}(i) < 0$&nbsp; spricht aus Sicht der anderen Symbole&nbsp; $(j &ne; i)$&nbsp; vieles dafür, dass&nbsp; $x_i = 1$&nbsp; ist.
+
*If&nbsp; $L_{\rm E}(i) < 0$&nbsp; from the point of view of the other symbols&nbsp; $(j &ne; i)$&nbsp; there is much to be said for&nbsp; $x_i = 1$&nbsp;.
  
  
Behandelt wird ausschließlich der&nbsp; $\text{SPC (4, 3, 4)}$, wobei für die Wahrscheinlichkeiten&nbsp; $p_i = {\rm Pr}(x_i = 1)$&nbsp; gilt:
+
Only the&nbsp; $\text{SPC (4, 3, 4)}$ is treated, where for the probabilities&nbsp; $p_i = {\rm Pr}(x_i = 1)$&nbsp; holds:
 
:$$p_1 = 0.2 \hspace{0.05cm}, \hspace{0.3cm}
 
:$$p_1 = 0.2 \hspace{0.05cm}, \hspace{0.3cm}
 
p_2 = 0.9 \hspace{0.05cm}, \hspace{0.3cm}  
 
p_2 = 0.9 \hspace{0.05cm}, \hspace{0.3cm}  
Line 23: Line 23:
 
p_4 = 0.6  \hspace{0.05cm}.$$
 
p_4 = 0.6  \hspace{0.05cm}.$$
  
Daraus ergeben sich die Apriori&ndash;$L$&ndash;Werte zu:
+
From this the apriori&ndash;$L$ values result to:
 
:$$L_{\rm A}(i) = {\rm ln} \hspace{0.1cm} \left [ \frac{{\rm Pr}(x_i = 0)}{{\rm Pr}(x_i = 1)}
 
:$$L_{\rm A}(i) = {\rm ln} \hspace{0.1cm} \left [ \frac{{\rm Pr}(x_i = 0)}{{\rm Pr}(x_i = 1)}
 
\right ] = {\rm ln} \hspace{0.1cm} \left [ \frac{1-p_i}{p_i}
 
\right ] = {\rm ln} \hspace{0.1cm} \left [ \frac{1-p_i}{p_i}
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''Hinweise:''
+
Hints:
* Die Aufgabe gehört zum Kapitel&nbsp; [[Channel_Coding/Soft-in_Soft-Out_Decoder| "Soft&ndash;in Soft&ndash;out Decoder"]].
+
*This exercise belongs to the chapter&nbsp; [[Channel_Coding/Soft-in_Soft-Out_Decoder|"Soft&ndash;in Soft&ndash;out Decoder"]].
*Bezug genommen wird insbesondere auf die Seite&nbsp; [[Channel_Coding/Soft-in_Soft-Out_Decoder#Calculation_of_extrinsic_LLRs|"Zur Berechnung der extrinsischen&nbsp; $L$&ndash;Werte"]].  
+
*Reference is made in particular to the page&nbsp; [[Channel_Coding/Soft-in_Soft-Out_Decoder#Calculation_of_extrinsic_LLRs|"Calculation of the extrinsic&nbsp; $L$ values"]].  
* In der Tabelle sind für&nbsp; $p_i = 0$&nbsp; bis&nbsp; $p_i = 1$&nbsp; mit Schrittweite $0.1$ (Spalte 1) angegeben:
+
* In the table are given for&nbsp; $p_i = 0$&nbsp; to&nbsp; $p_i = 1$&nbsp; with step size $0.1$ (column 1):
::In Spalte 2: &nbsp; die Wahrscheinlichkeit&nbsp; $q_i = {\rm Pr}(x_i = 0) = 1 - p_i$,
+
::In column 2: &nbsp; the probability&nbsp; $q_i = {\rm Pr}(x_i = 0) = 1 - p_i$,
::in Spalte 3: &nbsp; die Werte für&nbsp; $1 - 2p_i$,
+
::in column 3: &nbsp; the values for&nbsp; $1 - 2p_i$,
::in Spalte 4: &nbsp; die Apriori&ndash;$L$&ndash;Werte&nbsp; $L_i = \ln {\big [(1 - p_i)/p_ i \big ]} = L_{\rm A}(i)$.
+
::in column 4: &nbsp; the apriori $L$ values&nbsp; $L_i = \ln {\big [(1 - p_i)/p_ i \big ]} = L_{\rm A}(i)$.
* Der&nbsp; <i>Tangens Hyperbolicus</i>&nbsp; ($\tanh$)&nbsp; von $L_i/2$&nbsp; ist identisch mit&nbsp; $1-2p_i$ &nbsp; &#8658; &nbsp; Spalte 3.
+
* The&nbsp; <i>hyperbolic tangent</i>&nbsp; ($\tanh$)&nbsp; of $L_i/2$&nbsp; is identical to&nbsp; $1-2p_i$ &nbsp; &#8658; &nbsp; column 3.
* In der&nbsp; [[Aufgaben:Exercise_4.4Z:_Supplement_to_Exercise_4.4|"Aufgabe 4.4Z"]]&nbsp; wird gezeigt, dass für den extrinsischen&nbsp; $L$&ndash;Wert auch geschrieben werden kann:
+
* In the&nbsp; [[Aufgaben:Exercise_4.4Z:_Supplement_to_Exercise_4.4|"Exercise 4.4Z"]]&nbsp; it is shown that for the extrinsic&nbsp; $L$&ndash;value can also be written:
 
:$$L_{\rm E}(i) = {\rm ln} \hspace{0.2cm}  \frac{1 + \pi}{1 - \pi}\hspace{0.05cm}, \hspace{0.3cm}
 
:$$L_{\rm E}(i) = {\rm ln} \hspace{0.2cm}  \frac{1 + \pi}{1 - \pi}\hspace{0.05cm}, \hspace{0.3cm}
 
{\rm mit} \hspace{0.3cm} \pi = \prod\limits_{j \ne i}^{n} \hspace{0.25cm}(1-2p_j)
 
{\rm mit} \hspace{0.3cm} \pi = \prod\limits_{j \ne i}^{n} \hspace{0.25cm}(1-2p_j)
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===Fragebogen===
+
===Questions===
 
<quiz display=simple>
 
<quiz display=simple>
{Es gelte&nbsp; $p_1 = 0.2, \ p_2 = 0.9, \ p_3 = 0.3, \ p_4 = 0.6$. Berechnen Sie daraus die Apriori&ndash;$L$&ndash;Werte des&nbsp; $\text{SPC (4, 3, 4)}$&nbsp; für Bit 1 und Bit 2.
+
{It holds&nbsp; $p_1 = 0.2, \ p_2 = 0.9, \ p_3 = 0.3, \ p_4 = 0.6$. From this, calculate the apriori $L$ values of the&nbsp; $\text{SPC (4, 3, 4)}$&nbsp; for bit 1 and bit 2.
 
|type="{}"}
 
|type="{}"}
 
$L_{\rm A}(i = 1) \ = \ ${ 1.386 3% }
 
$L_{\rm A}(i = 1) \ = \ ${ 1.386 3% }
 
$L_{\rm A}(i = 2) \ = \ ${ -2.26291--2.13109 }
 
$L_{\rm A}(i = 2) \ = \ ${ -2.26291--2.13109 }
  
{Wie lauten die extrinsischen $L$&ndash;Werte für Bit 1 und Bit 2.
+
{What are the extrinsic $L$ values for bit 1 and bit 2.
 
|type="{}"}
 
|type="{}"}
 
$L_{\rm E}(i = 1) \ = \ ${ 0.128 3% }
 
$L_{\rm E}(i = 1) \ = \ ${ 0.128 3% }
 
$L_{\rm E}(i = 2) \ = \ ${ -0.09888--0.09312 }
 
$L_{\rm E}(i = 2) \ = \ ${ -0.09888--0.09312 }
  
{Welche Zusammenhänge bestehen zwischen&nbsp; $p_j$&nbsp; und&nbsp; $L_j = L_{\rm A}(j)$?
+
{What are the relationships between&nbsp; $p_j$&nbsp; and&nbsp; $L_j = L_{\rm A}(j)$?
 
|type="[]"}
 
|type="[]"}
 
+ Es gilt&nbsp; $p_j = 1/(1 + {\rm e}^ {L_j})$.
 
+ Es gilt&nbsp; $p_j = 1/(1 + {\rm e}^ {L_j})$.
Line 69: Line 69:
 
+ Es gilt&nbsp; $1-2p_j = \tanh {(L_j/2)}$.
 
+ Es gilt&nbsp; $1-2p_j = \tanh {(L_j/2)}$.
  
{Es gelte weiter&nbsp; $p_1 = 0.2, \ p_2 = 0.9, \ p_3$ und $p_4 = 0.6$. Berechnen Sie die extrinsischen $L$&ndash;Werte für Bit 3 und Bit 4. <br>Verwenden Sie hierzu verschiedene Gleichungen.
+
{It further&nbsp; $p_1 = 0.2, \ p_2 = 0.9, \ p_3$ and $p_4 = 0.6$. Calculate the extrinsic $L$ values for bit 3 and bit 4. <br>Use different equations for this purpose.
 
|type="{}"}
 
|type="{}"}
 
$L_{\rm E}(i = 3) \ = \ ${ 0.193 3% }
 
$L_{\rm E}(i = 3) \ = \ ${ 0.193 3% }
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</quiz>
 
</quiz>
  
===Musterlösung===
+
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''&nbsp; Für die Apriori&ndash;$L$&ndash;Werte der beiden ersten Bits des Codewortes gilt:
+
'''(1)'''&nbsp; For the apriori $L$ values of the first two bits of the code word:
 
:$$L_{\rm A}(i = 1) \hspace{-0.15cm} \ = \ \hspace{-0.15cm} {\rm ln} \hspace{0.1cm} \left [ \frac{1-p_1}{p_1} \right ] =  {\rm ln} \hspace{0.1cm} 4 \hspace{0.15cm}\underline{= +1.386}  
 
:$$L_{\rm A}(i = 1) \hspace{-0.15cm} \ = \ \hspace{-0.15cm} {\rm ln} \hspace{0.1cm} \left [ \frac{1-p_1}{p_1} \right ] =  {\rm ln} \hspace{0.1cm} 4 \hspace{0.15cm}\underline{= +1.386}  
 
  \hspace{0.05cm},$$
 
  \hspace{0.05cm},$$
Line 83: Line 83:
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
Die Werte können aus der vierten Spalte der auf der Angabenseite beigefügten  Tabelle abgelesen werden.
+
The values can be read from the fourth column of the table attached to the information page.
  
  
'''(2)'''&nbsp; Zur Berechnung des extrinsischen $L$&ndash;Wertes über das $i$&ndash;te Bit dürfen nur die Informationen über die drei anderen Bits $(j &ne; i)$ herangezogen werden. Mit der angegebenen Gleichung gilt:
+
'''(2)'''&nbsp; To calculate the extrinsic $L$ value over the $i$th bit, only the information about the other three bits $(j &ne; i)$ may be used. With the given equation holds:
 
:$$L_{\rm E}(i = 1) = {\rm ln} \hspace{0.2cm}  \frac{1 + \prod\limits_{j \ne 1} \hspace{0.25cm}(1-2p_j)}{1 - \prod\limits_{j \ne 1} \hspace{0.25cm}(1-2p_j)}
 
:$$L_{\rm E}(i = 1) = {\rm ln} \hspace{0.2cm}  \frac{1 + \prod\limits_{j \ne 1} \hspace{0.25cm}(1-2p_j)}{1 - \prod\limits_{j \ne 1} \hspace{0.25cm}(1-2p_j)}
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
*Für das Produkt erhält man entsprechend der dritten Spalte der [[Aufgaben:4.4_Extrinsische_L%E2%80%93Werte_beim_SPC|Tabelle]]:
+
*For the product, we obtain according to the third column of [[Aufgaben:Exercise_4.4:_Extrinsic_L-values_at_SPC|"table"]]:
 
:$$\prod\limits_{j =2, \hspace{0.05cm}3,\hspace{0.05cm} 4} \hspace{0.05cm}(1-2p_j) =  
 
:$$\prod\limits_{j =2, \hspace{0.05cm}3,\hspace{0.05cm} 4} \hspace{0.05cm}(1-2p_j) =  
 
(-0.8) \cdot (+0.4) \cdot (-0.2) = 0.064
 
(-0.8) \cdot (+0.4) \cdot (-0.2) = 0.064
Line 97: Line 97:
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
*Hinsichtlich Bit 2 erhält man entsprechend:
+
*In terms of bit 2, one obtains accordingly:
 
:$$\prod\limits_{j =1, \hspace{0.05cm}3,\hspace{0.05cm} 4} \hspace{0.05cm}(1-2p_j) =  
 
:$$\prod\limits_{j =1, \hspace{0.05cm}3,\hspace{0.05cm} 4} \hspace{0.05cm}(1-2p_j) =  
 
(+0.6) \cdot (+0.4) \cdot (-0.2) = -0.048
 
(+0.6) \cdot (+0.4) \cdot (-0.2) = -0.048
Line 105: Line 105:
  
  
'''(3)'''&nbsp; Für den Apriori&ndash;$L$&ndash;Wert gilt:
+
'''(3)'''&nbsp; For the apriori $L$ value holds:
 
:$$L_j = L_{\rm A}(j) = {\rm ln} \hspace{0.1cm} \left [ \frac{{\rm Pr}(x_j = 0)}{{\rm Pr}(x_j = 1)}
 
:$$L_j = L_{\rm A}(j) = {\rm ln} \hspace{0.1cm} \left [ \frac{{\rm Pr}(x_j = 0)}{{\rm Pr}(x_j = 1)}
 
\right ] = {\rm ln} \hspace{0.1cm} \left [ \frac{1-p_j}{p_j}
 
\right ] = {\rm ln} \hspace{0.1cm} \left [ \frac{1-p_j}{p_j}
Line 113: Line 113:
 
\hspace{0.05cm} .$$
 
\hspace{0.05cm} .$$
  
*Damit gilt auch:
+
*Thus also applies:
 
:$$1- 2 \cdot p_j =  1 - \frac{2}{1+{\rm e}^{L_j} } = \frac{1+{\rm e}^{L_j}-2}{1+{\rm e}^{L_j} }
 
:$$1- 2 \cdot p_j =  1 - \frac{2}{1+{\rm e}^{L_j} } = \frac{1+{\rm e}^{L_j}-2}{1+{\rm e}^{L_j} }
 
= \frac{{\rm e}^{L_j}-1}{{\rm e}^{L_j} +1}\hspace{0.05cm} .$$
 
= \frac{{\rm e}^{L_j}-1}{{\rm e}^{L_j} +1}\hspace{0.05cm} .$$
  
*Multipliziert man Zähler und Nenner noch mit ${\rm e}^{-L_j/2}$, so erhält man:
+
*Multiplying the numerator and denominator by ${\rm e}^{-L_j/2}$, we get:
 
:$$1- 2 \cdot p_j =  \frac{{\rm e}^{L_j/2}-{\rm e}^{-L_j/2}}{{\rm e}^{L_j/2}+{\rm e}^{-L_j/2}}={\rm tanh}  (L_j/2) \hspace{0.05cm} .$$
 
:$$1- 2 \cdot p_j =  \frac{{\rm e}^{L_j/2}-{\rm e}^{-L_j/2}}{{\rm e}^{L_j/2}+{\rm e}^{-L_j/2}}={\rm tanh}  (L_j/2) \hspace{0.05cm} .$$
  
*Somit sind <u>alle Lösungsvorschläge</u> richtig.  
+
*Thus <u>all proposed solutions</u> are correct.  
*Die Funktion <i>Tangens Hyperbolicus</i> findet man zum Beispiel tabellarisch in Formelsammlungen oder in der letzten Spalte der vorne angegebenen Tabelle.
+
*The function <i>hyperbolic tangent</i> can be found, for example, in tabular form in collections of formulas or in the last column of the table given in front.
  
  
'''(4)'''&nbsp; Wir berechnen $L_{\rm E}(i = 3)$ zunächst in gleicher Weise wie in der Teilaufgabe (2):
+
'''(4)'''&nbsp; We first calculate $L_{\rm E}(i = 3)$ in the same way as in subtask (2):
 
:$$\prod\limits_{j =1, \hspace{0.05cm}2,\hspace{0.05cm} 4} \hspace{0.05cm}(1-2p_j) =  
 
:$$\prod\limits_{j =1, \hspace{0.05cm}2,\hspace{0.05cm} 4} \hspace{0.05cm}(1-2p_j) =  
 
(+0.6) \cdot (-0.8) \cdot (-0.2) = +0.096
 
(+0.6) \cdot (-0.8) \cdot (-0.2) = +0.096
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  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
*Den extrinsischen $L$&ndash;Wert hinsichtlich des letzten Bits berechnen wir nach der Gleichung
+
*We calculate the extrinsic $L$ value with respect to the last bit according to the equation
 
:$$L_{\rm E}(i = 4) = {\rm ln} \hspace{0.2cm}  \frac{1 + \pi}{1 - \pi}\hspace{0.05cm}, \hspace{0.3cm}
 
:$$L_{\rm E}(i = 4) = {\rm ln} \hspace{0.2cm}  \frac{1 + \pi}{1 - \pi}\hspace{0.05cm}, \hspace{0.3cm}
 
{\rm mit} \hspace{0.3cm} \pi = {\rm tanh}(L_1/2) \cdot {\rm tanh}(L_2/2) \cdot {\rm tanh}(L_3/2)
 
{\rm mit} \hspace{0.3cm} \pi = {\rm tanh}(L_1/2) \cdot {\rm tanh}(L_2/2) \cdot {\rm tanh}(L_3/2)
 
  \hspace{0.05cm}.$$
 
  \hspace{0.05cm}.$$
  
*Damit ergibt sich entsprechend der obigen [[Aufgaben:4.4_Extrinsische_L%E2%80%93Werte_beim_SPC|Tabelle]]:
+
*This results in accordance with the above [[Aufgaben:Exercise_4.4:_Extrinsic_L-values_at_SPC|"table"]]:
 
:$$p_1 = 0.2 \hspace{0.2cm}\Rightarrow \hspace{0.2cm}
 
:$$p_1 = 0.2 \hspace{0.2cm}\Rightarrow \hspace{0.2cm}
 
L_1 = +1.386 \hspace{0.2cm}\Rightarrow \hspace{0.2cm}
 
L_1 = +1.386 \hspace{0.2cm}\Rightarrow \hspace{0.2cm}
Line 156: Line 156:
 
  = 0.4 \hspace{0.3cm}\Rightarrow \hspace{0.3cm}{\rm identisch \hspace{0.15cm}mit\hspace{0.15cm} }1-2\cdot p_3\hspace{0.05cm}.$$
 
  = 0.4 \hspace{0.3cm}\Rightarrow \hspace{0.3cm}{\rm identisch \hspace{0.15cm}mit\hspace{0.15cm} }1-2\cdot p_3\hspace{0.05cm}.$$
  
*Das Endergebnis lautet somit:
+
*The final result is thus:
 
:$$\pi = (+0.6) \cdot (-0.8) \cdot (+0.4) = -0.192
 
:$$\pi = (+0.6) \cdot (-0.8) \cdot (+0.4) = -0.192
 
\hspace{0.3cm}\Rightarrow \hspace{0.3cm}
 
\hspace{0.3cm}\Rightarrow \hspace{0.3cm}

Revision as of 19:44, 29 October 2022

Suitable auxiliary table

We consider again the  "single parity–check code". In such a  ${\rm SPC} \ (n, \, n-1, \, 2)$  the  $n$  bits of a codeword  $\underline{x}$  come from the  $k = n -1$  bits from the source sequence  $\underline{u}$  and only a single check bit  $p$  is added, such that the number of ones in the codeword is even:

$$\underline{x} = \big ( \hspace{0.03cm}x_1, \hspace{0.03cm} x_2, \hspace{0.05cm} \text{...} \hspace{0.05cm} , x_{n-1}, \hspace{0.03cm} x_n \hspace{0.03cm} \big ) = \big ( \hspace{0.03cm}u_1, \hspace{0.03cm} u_2, \hspace{0.05cm} \text{...} \hspace{0.05cm} , u_{k}, \hspace{0.03cm} p \hspace{0.03cm} \big )\hspace{0.03cm}. $$

The extrinsic information about the  $i$th code bit is formed over all other symbols  $(j ≠ i)$ . Therefore we write for the code word shorter by one bit:

$$\underline{x}^{(-i)} = \big ( \hspace{0.03cm}x_1, \hspace{0.05cm} \text{...} \hspace{0.05cm} , \hspace{0.03cm} x_{i-1}, \hspace{0.43cm} x_{i+1}, \hspace{0.05cm} \text{...} \hspace{0.05cm} , x_{n} \hspace{0.03cm} \big )\hspace{0.03cm}. $$

The extrinsic  $L$ value over the  $i$th code symbol reads with the  "Hamming–weight"  $w_{\rm H}$  of the truncated sequence  $\underline{x}^{(-i)}$:

$$L_{\rm E}(i) = \frac{{\rm Pr} \left [w_{\rm H}(\underline{x}^{(-i)})\hspace{0.15cm}{\rm ist \hspace{0.15cm} gerade} \hspace{0.05cm} | \hspace{0.05cm}\underline{y} \hspace{0.05cm}\right ]}{{\rm Pr} \left [w_{\rm H}(\underline{x}^{(-i)})\hspace{0.15cm}{\rm ist \hspace{0.15cm} ungerade} \hspace{0.05cm} | \hspace{0.05cm}\underline{y} \hspace{0.05cm}\right ]} \hspace{0.05cm}.$$
  • If the probability in the numerator is greater than that in the denominator, then  $L_{\rm E}(i) > 0$  and thus the a posteriori–$L$– value  $L_{\rm APP}(i) = L_{\rm A}(i) + L_{\rm E}(i)$  magnified, that is tends to be affected in the direction of the symbol  $x_i = 0$ .
  • If  $L_{\rm E}(i) < 0$  from the point of view of the other symbols  $(j ≠ i)$  there is much to be said for  $x_i = 1$ .


Only the  $\text{SPC (4, 3, 4)}$ is treated, where for the probabilities  $p_i = {\rm Pr}(x_i = 1)$  holds:

$$p_1 = 0.2 \hspace{0.05cm}, \hspace{0.3cm} p_2 = 0.9 \hspace{0.05cm}, \hspace{0.3cm} p_3 = 0.3 \hspace{0.05cm}, \hspace{0.3cm} p_4 = 0.6 \hspace{0.05cm}.$$

From this the apriori–$L$ values result to:

$$L_{\rm A}(i) = {\rm ln} \hspace{0.1cm} \left [ \frac{{\rm Pr}(x_i = 0)}{{\rm Pr}(x_i = 1)} \right ] = {\rm ln} \hspace{0.1cm} \left [ \frac{1-p_i}{p_i} \right ] \hspace{0.05cm}.$$





Hints:

In column 2:   the probability  $q_i = {\rm Pr}(x_i = 0) = 1 - p_i$,
in column 3:   the values for  $1 - 2p_i$,
in column 4:   the apriori $L$ values  $L_i = \ln {\big [(1 - p_i)/p_ i \big ]} = L_{\rm A}(i)$.
  • The  hyperbolic tangent  ($\tanh$)  of $L_i/2$  is identical to  $1-2p_i$   ⇒   column 3.
  • In the  "Exercise 4.4Z"  it is shown that for the extrinsic  $L$–value can also be written:
$$L_{\rm E}(i) = {\rm ln} \hspace{0.2cm} \frac{1 + \pi}{1 - \pi}\hspace{0.05cm}, \hspace{0.3cm} {\rm mit} \hspace{0.3cm} \pi = \prod\limits_{j \ne i}^{n} \hspace{0.25cm}(1-2p_j) \hspace{0.05cm}.$$


Questions

1

It holds  $p_1 = 0.2, \ p_2 = 0.9, \ p_3 = 0.3, \ p_4 = 0.6$. From this, calculate the apriori $L$ values of the  $\text{SPC (4, 3, 4)}$  for bit 1 and bit 2.

$L_{\rm A}(i = 1) \ = \ $

$L_{\rm A}(i = 2) \ = \ $

2

What are the extrinsic $L$ values for bit 1 and bit 2.

$L_{\rm E}(i = 1) \ = \ $

$L_{\rm E}(i = 2) \ = \ $

3

What are the relationships between  $p_j$  and  $L_j = L_{\rm A}(j)$?

Es gilt  $p_j = 1/(1 + {\rm e}^ {L_j})$.
Es gilt  $1-2p_j = ({\rm e}^ {L_j} - 1) \ / \ ({\rm e}^ {L_j} + 1)$.
Es gilt  $1-2p_j = \tanh {(L_j/2)}$.

4

It further  $p_1 = 0.2, \ p_2 = 0.9, \ p_3$ and $p_4 = 0.6$. Calculate the extrinsic $L$ values for bit 3 and bit 4.
Use different equations for this purpose.

$L_{\rm E}(i = 3) \ = \ $

$L_{\rm E}(i = 4) \ = \ $


Solution

(1)  For the apriori $L$ values of the first two bits of the code word:

$$L_{\rm A}(i = 1) \hspace{-0.15cm} \ = \ \hspace{-0.15cm} {\rm ln} \hspace{0.1cm} \left [ \frac{1-p_1}{p_1} \right ] = {\rm ln} \hspace{0.1cm} 4 \hspace{0.15cm}\underline{= +1.386} \hspace{0.05cm},$$
$$L_{\rm A}(i = 2) \hspace{-0.15cm} \ = \ \hspace{-0.15cm} {\rm ln} \hspace{0.1cm} \left [ \frac{1-p_2}{p_2} \right ] = {\rm ln} \hspace{0.1cm} 1/9 \hspace{0.15cm}\underline{= -2.197} \hspace{0.05cm}.$$

The values can be read from the fourth column of the table attached to the information page.


(2)  To calculate the extrinsic $L$ value over the $i$th bit, only the information about the other three bits $(j ≠ i)$ may be used. With the given equation holds:

$$L_{\rm E}(i = 1) = {\rm ln} \hspace{0.2cm} \frac{1 + \prod\limits_{j \ne 1} \hspace{0.25cm}(1-2p_j)}{1 - \prod\limits_{j \ne 1} \hspace{0.25cm}(1-2p_j)} \hspace{0.05cm}.$$
  • For the product, we obtain according to the third column of "table":
$$\prod\limits_{j =2, \hspace{0.05cm}3,\hspace{0.05cm} 4} \hspace{0.05cm}(1-2p_j) = (-0.8) \cdot (+0.4) \cdot (-0.2) = 0.064 \hspace{0.05cm}\hspace{0.3cm} \Rightarrow \hspace{0.3cm}L_{\rm E}(i = 1) = {\rm ln} \hspace{0.2cm} \frac{1 + 0.064}{1 - 0.064} = {\rm ln} \hspace{0.1cm} (1.137)\hspace{0.15cm}\underline{= +0.128} \hspace{0.05cm}.$$
  • In terms of bit 2, one obtains accordingly:
$$\prod\limits_{j =1, \hspace{0.05cm}3,\hspace{0.05cm} 4} \hspace{0.05cm}(1-2p_j) = (+0.6) \cdot (+0.4) \cdot (-0.2) = -0.048 \hspace{0.05cm}\hspace{0.3cm} \Rightarrow \hspace{0.3cm}L_{\rm E}(i = 2) = {\rm ln} \hspace{0.2cm} \frac{1 -0.048}{1 +0.048} = {\rm ln} \hspace{0.1cm} (0.908)\hspace{0.15cm}\underline{= -0.096} \hspace{0.05cm}.$$


(3)  For the apriori $L$ value holds:

$$L_j = L_{\rm A}(j) = {\rm ln} \hspace{0.1cm} \left [ \frac{{\rm Pr}(x_j = 0)}{{\rm Pr}(x_j = 1)} \right ] = {\rm ln} \hspace{0.1cm} \left [ \frac{1-p_j}{p_j} \right ]\hspace{0.3cm} \Rightarrow \hspace{0.3cm} 1-p_j = p_j \cdot {\rm e}^{L_j} \hspace{0.3cm} \Rightarrow \hspace{0.3cm} p_j = \frac{1}{1+{\rm e}^{L_j} } \hspace{0.05cm} .$$
  • Thus also applies:
$$1- 2 \cdot p_j = 1 - \frac{2}{1+{\rm e}^{L_j} } = \frac{1+{\rm e}^{L_j}-2}{1+{\rm e}^{L_j} } = \frac{{\rm e}^{L_j}-1}{{\rm e}^{L_j} +1}\hspace{0.05cm} .$$
  • Multiplying the numerator and denominator by ${\rm e}^{-L_j/2}$, we get:
$$1- 2 \cdot p_j = \frac{{\rm e}^{L_j/2}-{\rm e}^{-L_j/2}}{{\rm e}^{L_j/2}+{\rm e}^{-L_j/2}}={\rm tanh} (L_j/2) \hspace{0.05cm} .$$
  • Thus all proposed solutions are correct.
  • The function hyperbolic tangent can be found, for example, in tabular form in collections of formulas or in the last column of the table given in front.


(4)  We first calculate $L_{\rm E}(i = 3)$ in the same way as in subtask (2):

$$\prod\limits_{j =1, \hspace{0.05cm}2,\hspace{0.05cm} 4} \hspace{0.05cm}(1-2p_j) = (+0.6) \cdot (-0.8) \cdot (-0.2) = +0.096 \hspace{0.05cm}\hspace{0.3cm} \Rightarrow \hspace{0.3cm}L_{\rm E}(i = 3) = {\rm ln} \hspace{0.2cm} \frac{1 +0.096}{1 -0.096} = {\rm ln} \hspace{0.1cm} (1.212)\hspace{0.15cm}\underline{= +0.193} \hspace{0.05cm}.$$
  • We calculate the extrinsic $L$ value with respect to the last bit according to the equation
$$L_{\rm E}(i = 4) = {\rm ln} \hspace{0.2cm} \frac{1 + \pi}{1 - \pi}\hspace{0.05cm}, \hspace{0.3cm} {\rm mit} \hspace{0.3cm} \pi = {\rm tanh}(L_1/2) \cdot {\rm tanh}(L_2/2) \cdot {\rm tanh}(L_3/2) \hspace{0.05cm}.$$
  • This results in accordance with the above "table":
$$p_1 = 0.2 \hspace{0.2cm}\Rightarrow \hspace{0.2cm} L_1 = +1.386 \hspace{0.2cm}\Rightarrow \hspace{0.2cm} L_1/2 = +0.693 \hspace{0.2cm} \Rightarrow \hspace{0.2cm} {\rm tanh}(L_1/2) = \frac{{\rm e}^{+0.693}-{\rm e}^{-0.693}}{{\rm e}^{+0.693}+{\rm e}^{-0.693}} = 0.6 \hspace{0.3cm}\Rightarrow \hspace{0.3cm}{\rm identisch \hspace{0.15cm}mit\hspace{0.15cm} }1-2\cdot p_1\hspace{0.05cm},$$
$$p_2 = 0.9 \hspace{0.2cm}\Rightarrow \hspace{0.2cm} L_2 = -2.197 \hspace{0.2cm}\Rightarrow \hspace{0.2cm} L_2/2 = -1.099\hspace{0.2cm} \Rightarrow \hspace{0.2cm} {\rm tanh}(L_2/2) = \frac{{\rm e}^{-1.099}-{\rm e}^{+1.099}}{{\rm e}^{-1.099}+{\rm e}^{+1.099}} = -0.8 \hspace{0.3cm}\Rightarrow \hspace{0.3cm}{\rm identisch \hspace{0.15cm}mit\hspace{0.15cm} }1-2\cdot p_2\hspace{0.05cm},$$
$$p_3 = 0.3 \hspace{0.2cm}\Rightarrow \hspace{0.2cm} L_3 = 0.847 \hspace{0.2cm}\Rightarrow \hspace{0.2cm} L_3/2 = +0.419 \hspace{0.2cm} \Rightarrow \hspace{0.2cm} {\rm tanh}(L_3/2) = \frac{{\rm e}^{+0.419}-{\rm e}^{-0.419}}{{\rm e}^{+0.419}+{\rm e}^{-0.419}} = 0.4 \hspace{0.3cm}\Rightarrow \hspace{0.3cm}{\rm identisch \hspace{0.15cm}mit\hspace{0.15cm} }1-2\cdot p_3\hspace{0.05cm}.$$
  • The final result is thus:
$$\pi = (+0.6) \cdot (-0.8) \cdot (+0.4) = -0.192 \hspace{0.3cm}\Rightarrow \hspace{0.3cm} L_{\rm E}(i = 4) = {\rm ln} \hspace{0.2cm} \frac{1 -0.192}{1 +0.192}\hspace{0.15cm}\underline{= -0.389} \hspace{0.05cm}.$$