Difference between revisions of "Aufgaben:Exercise 3.09Z: Viterbi Algorithm again"

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{{quiz-Header|Buchseite=Channel_Coding/Decoding_of_Convolutional_Codes}}
 
{{quiz-Header|Buchseite=Channel_Coding/Decoding_of_Convolutional_Codes}}
  
[[File:P_ID2656__KC_Z_3_8_neu.png|right|frame|Trellis for a rate 1/2 code, memory  $m = 1$]]
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[[File:P_ID2656__KC_Z_3_8_neu.png|right|frame|Trellis for a rate-1/2 code and memory  $m = 1$]]
The diagram shows the trellis of the convolutional code according to  [[Aufgaben:Exercise_3.6:_State_Transition_Diagram| "Exercise 3.6"]], characterized by the following quantities:
+
The diagram shows the trellis of the convolutional code according to  [[Aufgaben:Exercise_3.6:_State_Transition_Diagram|$\text{Exercise 3.6}$]],  characterized by the following quantities:
 
* Rate 1/2  ⇒   $k = 1, \ n = 2$,
 
* Rate 1/2  ⇒   $k = 1, \ n = 2$,
 +
 
* memory  $m = 1$,
 
* memory  $m = 1$,
 +
 
* transfer function matrix  $\mathbf{G}(D) = (1, \ 1 + D)$,
 
* transfer function matrix  $\mathbf{G}(D) = (1, \ 1 + D)$,
* length of information sequence:  $L = 4$,
+
 
 +
* length of the information sequence:  $L = 4$,
 +
 
 
* sequence length including termination:  $L\hspace{0.05cm}' = L + m = 5$.
 
* sequence length including termination:  $L\hspace{0.05cm}' = L + m = 5$.
  
  
On the basis of this representation, the Viterbi decoding is to be understood step by step, starting from the following reception sequence:   $\underline{y} = (11, \, 01, \, 01, \, 11, \, 01)$.
+
On the basis of this representation,  the Viterbi decoding is to be understood step-by-step,  starting from the following received sequence:    
 +
:$$\underline{y} = (11, \, 01, \, 01, \, 11, \, 01).$$
  
Drawn into the trellis are:
+
Into the trellis are drawn:
* The initial value  ${\it \Gamma}_0(S_0)$  for the Viterbi–algorithm, which is always chosen to  $0$ .
+
* The initial value  ${\it \Gamma}_0(S_0)$  for the Viterbi algorithm,  which is always chosen to  $0$.
* The two branch metrics for the first decoding step  $(i = 1)$  are obtained with  $\underline{y}_1 = (11)$  as follows:
+
 
 +
* The two error values for the first decoding step  $(i = 1)$  are obtained with  $\underline{y}_1 = (11)$  as follows:
 
:$${\it \Gamma}_1(S_0) \hspace{-0.15cm} \ = \ \hspace{-0.15cm} {\it \Gamma}_0(S_0) + d_{\rm H} \big ((00)\hspace{0.05cm},\hspace{0.05cm} (11) \big )  = 2  \hspace{0.05cm},$$
 
:$${\it \Gamma}_1(S_0) \hspace{-0.15cm} \ = \ \hspace{-0.15cm} {\it \Gamma}_0(S_0) + d_{\rm H} \big ((00)\hspace{0.05cm},\hspace{0.05cm} (11) \big )  = 2  \hspace{0.05cm},$$
 
:$${\it \Gamma}_1(S_1) \hspace{-0.15cm} \ = \ \hspace{-0.15cm} {\it \Gamma}_0(S_0) + d_{\rm H} \big ((11)\hspace{0.05cm},\hspace{0.05cm} (11) \big )  = 0  \hspace{0.05cm}.$$
 
:$${\it \Gamma}_1(S_1) \hspace{-0.15cm} \ = \ \hspace{-0.15cm} {\it \Gamma}_0(S_0) + d_{\rm H} \big ((11)\hspace{0.05cm},\hspace{0.05cm} (11) \big )  = 0  \hspace{0.05cm}.$$
  
* The branch metrics to step  $i = 2$   ⇒   $\underline{y}_2 = (01)$  are obtained by the following comparisons:
+
* The error values for step  $i = 2$   ⇒   $\underline{y}_2 = (01)$  are obtained by the following comparisons:
 
:$${\it \Gamma}_2(S_0) \hspace{-0.15cm} \ = \ \hspace{-0.15cm}{\rm min} \left [{\it \Gamma}_{1}(S_0) + d_{\rm H} \big ((00)\hspace{0.05cm},\hspace{0.05cm} (01) \big )\hspace{0.05cm}, \hspace{0.2cm}{\it \Gamma}_{1}(S_1) + d_{\rm H} \big ((01)\hspace{0.05cm},\hspace{0.05cm} (01) \big ) \right ] $$
 
:$${\it \Gamma}_2(S_0) \hspace{-0.15cm} \ = \ \hspace{-0.15cm}{\rm min} \left [{\it \Gamma}_{1}(S_0) + d_{\rm H} \big ((00)\hspace{0.05cm},\hspace{0.05cm} (01) \big )\hspace{0.05cm}, \hspace{0.2cm}{\it \Gamma}_{1}(S_1) + d_{\rm H} \big ((01)\hspace{0.05cm},\hspace{0.05cm} (01) \big ) \right ] $$
 
:$$\Rightarrow\hspace{0.3cm} {\it \Gamma}_2(S_0) \hspace{-0.15cm} \ = \ \hspace{-0.15cm} {\rm min} \big [ 2+1\hspace{0.05cm},\hspace{0.05cm} 0+0 \big ] = 0\hspace{0.05cm},$$
 
:$$\Rightarrow\hspace{0.3cm} {\it \Gamma}_2(S_0) \hspace{-0.15cm} \ = \ \hspace{-0.15cm} {\rm min} \big [ 2+1\hspace{0.05cm},\hspace{0.05cm} 0+0 \big ] = 0\hspace{0.05cm},$$
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In the same way you are to
+
In the same way you are  
* compute the branch metrics at time points  $i = 3, \ i = 4$  and  $i = 5$  (termination), and  
+
* to compute the error values at time points  $i = 3, \ i = 4$  and  $i = 5$  $($termination$)$,  and
* eliminate the less favorable paths to a node  ${\it \Gamma}_i(S_{\mu})$  in each case. In the graph this is indicated by dotted lines for  $i = 2$ .
+
 +
* to eliminate the less favorable paths to a node  ${\it \Gamma}_i(S_{\mu})$  in each case;  in the graph this is indicated by dotted lines for  $i = 2$ .
  
  
Then the continuous path from  ${\it \Gamma}_0(S_0)$  to  ${\it \Gamma}_5(S_0)$  is to be found, where the backward direction is recommended.  
+
⇒   Then the continuous path from  ${\it \Gamma}_0(S_0)$  to  ${\it \Gamma}_5(S_0)$  is to be found,  where the backward direction is recommended.  If one follows the found path in forward direction,  one recognizes:
 +
* the most likely decoded sequence  $\underline{z}$  $($ideally equal  $\underline{x})$  by the labels,
  
If one follows the found path in forward direction, one recognizes.
 
* the most likely code sequence  $\underline{z}$  $($ideally equal  $\underline{x})$  by the labels,
 
 
* the most probable information sequence  $\underline{v}$  $($ideally equal  $\underline{u})$  at the colors.  
 
* the most probable information sequence  $\underline{v}$  $($ideally equal  $\underline{u})$  at the colors.  
  
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+
<u>Hints:</u>&nbsp; This exercise belongs to the chapter&nbsp; [[Channel_Coding/Decoding_of_Convolutional_Codes|"Decoding of Convolutional Codes"]].
 
 
Hints:
 
* This exercise belongs to the chapter&nbsp; [[Channel_Coding/Decoding_of_Convolutional_Codes| "Decoding of Convolutional Codes"]].
 
 
   
 
   
  

Revision as of 12:57, 18 November 2022

Trellis for a rate-1/2 code and memory  $m = 1$

The diagram shows the trellis of the convolutional code according to  $\text{Exercise 3.6}$,  characterized by the following quantities:

  • Rate 1/2  ⇒   $k = 1, \ n = 2$,
  • memory  $m = 1$,
  • transfer function matrix  $\mathbf{G}(D) = (1, \ 1 + D)$,
  • length of the information sequence:  $L = 4$,
  • sequence length including termination:  $L\hspace{0.05cm}' = L + m = 5$.


On the basis of this representation,  the Viterbi decoding is to be understood step-by-step,  starting from the following received sequence:  

$$\underline{y} = (11, \, 01, \, 01, \, 11, \, 01).$$

Into the trellis are drawn:

  • The initial value  ${\it \Gamma}_0(S_0)$  for the Viterbi algorithm,  which is always chosen to  $0$.
  • The two error values for the first decoding step  $(i = 1)$  are obtained with  $\underline{y}_1 = (11)$  as follows:
$${\it \Gamma}_1(S_0) \hspace{-0.15cm} \ = \ \hspace{-0.15cm} {\it \Gamma}_0(S_0) + d_{\rm H} \big ((00)\hspace{0.05cm},\hspace{0.05cm} (11) \big ) = 2 \hspace{0.05cm},$$
$${\it \Gamma}_1(S_1) \hspace{-0.15cm} \ = \ \hspace{-0.15cm} {\it \Gamma}_0(S_0) + d_{\rm H} \big ((11)\hspace{0.05cm},\hspace{0.05cm} (11) \big ) = 0 \hspace{0.05cm}.$$
  • The error values for step  $i = 2$   ⇒   $\underline{y}_2 = (01)$  are obtained by the following comparisons:
$${\it \Gamma}_2(S_0) \hspace{-0.15cm} \ = \ \hspace{-0.15cm}{\rm min} \left [{\it \Gamma}_{1}(S_0) + d_{\rm H} \big ((00)\hspace{0.05cm},\hspace{0.05cm} (01) \big )\hspace{0.05cm}, \hspace{0.2cm}{\it \Gamma}_{1}(S_1) + d_{\rm H} \big ((01)\hspace{0.05cm},\hspace{0.05cm} (01) \big ) \right ] $$
$$\Rightarrow\hspace{0.3cm} {\it \Gamma}_2(S_0) \hspace{-0.15cm} \ = \ \hspace{-0.15cm} {\rm min} \big [ 2+1\hspace{0.05cm},\hspace{0.05cm} 0+0 \big ] = 0\hspace{0.05cm},$$
$${\it \Gamma}_2(S_1) \hspace{-0.15cm} \ = \ \hspace{-0.15cm}{\rm min} \left [{\it \Gamma}_{1}(S_0) + d_{\rm H} \big ((11)\hspace{0.05cm},\hspace{0.05cm} (01) \big )\hspace{0.05cm}, \hspace{0.2cm}{\it \Gamma}_{1}(S_1) + d_{\rm H} \big ((10)\hspace{0.05cm},\hspace{0.05cm} (01) \big ) \right ]$$
$$\Rightarrow\hspace{0.3cm} {\it \Gamma}_2(S_1) \hspace{-0.15cm} \ = \ \hspace{-0.15cm} {\rm min} \big [ 2+1\hspace{0.05cm},\hspace{0.05cm} 0+2 \big ] = 2\hspace{0.05cm}.$$


In the same way you are

  • to compute the error values at time points  $i = 3, \ i = 4$  and  $i = 5$  $($termination$)$,  and
  • to eliminate the less favorable paths to a node  ${\it \Gamma}_i(S_{\mu})$  in each case;  in the graph this is indicated by dotted lines for  $i = 2$ .


⇒   Then the continuous path from  ${\it \Gamma}_0(S_0)$  to  ${\it \Gamma}_5(S_0)$  is to be found,  where the backward direction is recommended.  If one follows the found path in forward direction,  one recognizes:

  • the most likely decoded sequence  $\underline{z}$  $($ideally equal  $\underline{x})$  by the labels,
  • the most probable information sequence  $\underline{v}$  $($ideally equal  $\underline{u})$  at the colors.




Hints:  This exercise belongs to the chapter  "Decoding of Convolutional Codes".



Questions

1

Calculate the minimum branch metrics for time  $i = 3$.

${\it \Gamma}_3(S_0) \ = \ $

${\it \Gamma}_3(S_1) \ = \ $

2

Calculate the minimum branch metrics for time  $i = 4$.

${\it \Gamma}_4(S_0) \ = \ $

${\it \Gamma}_4(S_1) \ = \ $

3

Calculate the minimum branch metrics for time  $i = 5$ (end).

${\it \Gamma}_5(S_0) \ = \ $

4

What are the final results of the Viterbi algorithm:

$\underline{z} = (11, \, 01, \, 00, \, 11, \, 01)$.
$\underline{z} = (11, \, 01, \, 11, \, 01, \, 00)$.
$\underline{v} = (1, \, 0, \, 0, \, 1, \, 0)$.
$\underline{v} = (1, \, 0, \, 1, \, 0, \, 0)$.

5

What decision would have been made without scheduling?

The same,
another.


Solution

(1) 
Trellis with branch metrics
Starting from  ${\it \Gamma}_2(S_0) = 0, \ {\it \Gamma}_2(S_1) = 2$ we get $\underline{y}_3 = (01)$:
$${\it \Gamma}_3(S_0) \hspace{-0.15cm} \ = \ \hspace{-0.15cm} {\rm min} \left [0 + d_{\rm H} \big ((00), (01) \big ), \hspace{0.05cm}2 + d_{\rm H} \big ((01), (01) \big ) \right ] = {\rm min} \left [ 0+1\hspace{0.05cm},\hspace{0.05cm} 2+0 \right ] \hspace{0.15cm}\underline{= 1}\hspace{0.05cm},$$
$${\it \Gamma}_3(S_1) \hspace{-0.15cm} \ = \ \hspace{-0.15cm}{\rm min} \left [0 + d_{\rm H} \big ((11), (01) \big ), \hspace{0.05cm}2 + d_{\rm H} \big ((10), (01) \big ) \right ] {\rm min} \left [ 0+1\hspace{0.05cm},\hspace{0.05cm} 2+2 \right ] \hspace{0.15cm}\underline{= 1}\hspace{0.05cm}.$$

Thus, eliminated are the two subpaths that start from state $S_1$ at time $i = 2$ (i.e., at the third decoding step)   ⇒   Dotted in the graph.


(2)  Analogous to subtask (1), we obtain with  $y_4 = (11)$:

$${\it \Gamma}_4(S_0) \hspace{-0.15cm} \ = \ \hspace{-0.15cm}{\rm min} \left [1 + d_{\rm H} \big ((00), (11) \big ), \hspace{0.05cm}1 + d_{\rm H} \big ((01), (11) \big ) \right ] = {\rm min} \left [ 1+2\hspace{0.05cm},\hspace{0.05cm} 1+1 \right ] \hspace{0.15cm}\underline{= 2}\hspace{0.05cm},$$
$${\it \Gamma}_4(S_1) \hspace{-0.15cm} \ = \ \hspace{-0.15cm}{\rm min} \left [1 + d_{\rm H} \big ((11), (11) \big ), \hspace{0.05cm}1 + d_{\rm H} \big ((10), (11) \big ) \right ] ={\rm min} \left [ 1+0\hspace{0.05cm},\hspace{0.05cm} 1+1 \right ] \hspace{0.15cm}\underline{= 1}\hspace{0.05cm}$$

⇒   Elimination in the fourth decoding step of the two subpaths $S_0 → S_0$ and $S_1 → S_1$.


Path finding

(3)  Für $i = 5$   ⇒   "Termination" is obtained with  $\underline{y}_5 = (01)$:

$${\it \Gamma}_5(S_0) \hspace{-0.15cm} \ = \ \hspace{-0.15cm}{\rm min} \left [2 + d_{\rm H} \big ((00), (01) \big ), \hspace{0.05cm}1 + d_{\rm H} \big ((01), (01) \big ) \right ] {\rm min} \left [ 2+1\hspace{0.05cm},\hspace{0.05cm} 1+0 \right ] \hspace{0.15cm}\underline{= 1}\hspace{0.05cm}.$$

To be eliminated here is the subpath $S_0 → S_0$.


(4)  The backward search of the continuous path from ${\it \Gamma}_5(S_0)$ to ${\it \Gamma}_0(S_0)$ yields

$$S_0 ← S_1 ← S_0 ← S_0 ← S_1 ← S_0.$$

In the forward direction, this yields the path $S_0 → S_1 → S_0 → S_0 → S_1 → S_0$ and thus the

  • the most likely code sequence $\underline{z} = (11, \, 01, \, 00, \, 11, \, 01)$,
  • the most likely information sequence $\underline{v} = (1, \, 0, \, 0, \, 1, \, 0)$.


Thus, the proposed solutions 1 and 3 are correct:

  • A comparison with the given received vector $\underline{y} = (11, \, 01, \, 01, \, 11, \, 01)$ shows that the sixth bit was corrupted during transmission.


(5)  Without termination ⇒ final decision at $i = 4$, there would have been two continuous paths:

  • from $S_0 → S_1 → S_0 → S_1 → S_0$ (shown in yellow),
  • from $S_0 → S_1 → S_0 → S_0 → S_1$ (the ultimately correct path).


The constraint decision at time $i = 4$ would have led here to the second path and thus to the result $\underline{v} = (1, \, 0, \, 0, \, 1)$ because of ${\it \Gamma}_4(S_1) < {\it \Gamma}_4(S_0)$.

  • In the considered example, therefore, to the same decision as in subtask (4) with termination bit.
  • However, there are many constellations where only the termination bit enables the correct and safe decision.