Difference between revisions of "Aufgaben:Exercise 4.7Z: Principle of Syndrome Decoding"

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{{quiz-Header|Buchseite=Channel_Coding/The_Basics_of_Product_Codes}}
 
{{quiz-Header|Buchseite=Channel_Coding/The_Basics_of_Product_Codes}}
  
[[File:P_ID3013__KC_Z_4_7_v1.png|right|frame|Coset leader for the code under consideration  $\rm HC \ (7, \ 4, \ 3)$]]
+
[[File:EN KC T 4 2 S2b v2 neu.png|right|frame|Syndrome table for code  $\mathcal{C}_1$]]  
The syndrome decoding was already treated in detail in the chapter  [[Channel_Coding/Decoding_of_Linear_Block_Codes| "Decoding of linear block codes"]] . With all Hamming codes, which are as well known perfect, this gives a decoding result as good as with the (generally) clearly more complicated maximum likelihood decoding.
+
The syndrome decoding was already treated in detail in the chapter  [[Channel_Coding/Decoding_of_Linear_Block_Codes| "Decoding of Linear Block Codes"]].   
 +
 
 +
With all Hamming codes,  which are as well known perfect,  this gives a decoding result as good as with the  $($generally$)$ clearly more complicated maximum likelihood decoding.
  
 
For syndrome decoding one proceeds as follows:
 
For syndrome decoding one proceeds as follows:
* One forms the syndrome from the received vector  $\underline{y}$  of length  $n$  and the parity-check matrix  $\mathbf{H}$ :
+
* One forms the syndrome from the received vector  $\underline{y}$  of length  $n$  and the parity-check matrix  $\mathbf{H}$:
 
:$$\underline{s} = \underline{y} \cdot { \boldsymbol{\rm H}}^{\rm T} \in {\rm GF}(2^m)
 
:$$\underline{s} = \underline{y} \cdot { \boldsymbol{\rm H}}^{\rm T} \in {\rm GF}(2^m)
 
   \hspace{0.05cm},  \hspace{0.5cm}{\rm Note\hspace{-0.10cm}:} \hspace{0.15cm}m = n-k \hspace{0.05cm}. $$
 
   \hspace{0.05cm},  \hspace{0.5cm}{\rm Note\hspace{-0.10cm}:} \hspace{0.15cm}m = n-k \hspace{0.05cm}. $$
  
* The received word  $\underline{y} = \underline{x} \ {\rm (code\:word)} + \underline{e} \ {\rm (error\:vector)}$  is not necessarily an element of  ${\rm GF}(2^m)$, but certainly an element of  ${\rm GF}(2^n)$  and it holds because of  $\underline{x} \cdot \mathbf{H}^{\rm T} = \underline{0}$  equally:
+
* The received word  $\underline{y} = \underline{x} \ {\rm (code\:word)} + \underline{e} \ {\rm (error\:vector)}$  is not necessarily an element of  ${\rm GF}(2^m)$,  but certainly an element of  ${\rm GF}(2^n)$  and it holds because of   $\underline{x} \cdot \mathbf{H}^{\rm T} = \underline{0}$   equally:
 
:$$\underline{s} = \underline{e} \cdot { \boldsymbol{\rm H}}^{\rm T}\hspace{0.05cm}. $$
 
:$$\underline{s} = \underline{e} \cdot { \boldsymbol{\rm H}}^{\rm T}\hspace{0.05cm}. $$
  
* Many error patterns  $\underline{e}$  lead to the same syndrome  $\underline{s}$. One now groups those error patterns with the same syndrome  $\underline{s}_{\mu}$  to the coset  ${\it \Psi}_{\mu}$ .
+
* Many error patterns  $\underline{e}$  lead to the same syndrome  $\underline{s}$. One now groups those error patterns with the same syndrome  $\underline{s}_{\mu}$  to the  "coset  ${\it \Psi}_{\mu}$".
  
* The coset leader  $\underline{e}_{\mu}$  is the error vector that has the lowest Hamming weight within the class  ${\it \Psi}_{\mu}$  and is accordingly the most probable.
+
* The  "coset leader"  $\underline{e}_{\mu}$  is the error vector that has the lowest Hamming weight within the class  ${\it \Psi}_{\mu}$  and is accordingly the most probable.
  
  
The table above shows the list of minor class leaders  $\underline{e}_{\mu}$  for each  $\underline{s}_{\mu}$  in the Hamming code  $\rm HC \ (7, \ 4, \ 3)$. This table is needed for the subtask '''(1)'''.
+
The table above shows the list of the class leaders  $\underline{e}_{\mu}$  for each  $\underline{s}_{\mu}$  in the Hamming code  $\rm HC \ (7, 4, 3)$. This table is needed for the subtask  '''(1)'''.
  
A similar table is to be created for the truncated Hamming code  $\rm HC \ (6, \ 3, \ 3)$ . This has already been used in the  [[Aufgaben:Exercise_4.6:_Product_Code_Generation| "Exercise 4.6"]]  and the  [[Aufgaben:Exercise_4.6Z:_Basics_of_Product_Codes| "Exercise 4.6Z"]]  and is given by its generator matrix:
+
A similar table is to be created for the truncated Hamming code  $\rm HC \ (6, 3, 3)$.  This has already been used in the  [[Aufgaben:Exercise_4.6:_Product_Code_Generation|$\text{Exercise 4.6}$]]  and the  [[Aufgaben:Exercise_4.6Z:_Basics_of_Product_Codes| $\text{Exercise 4.6Z}$]]  and is given by its generator matrix:
 
:$${ \boldsymbol{\rm G}}  
 
:$${ \boldsymbol{\rm G}}  
 
=  \begin{pmatrix}
 
=  \begin{pmatrix}
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\end{pmatrix} \hspace{0.05cm}.$$
 
\end{pmatrix} \hspace{0.05cm}.$$
  
Unlike the original  $\rm (7, \ 4, \ 3)$ Hamming code, the shortened  $\rm (6, \ 3, \ 3)$– Hamming code is not perfect, so a single-w
+
Unlike the original  $\rm (7, 4, 3)$  Hamming code,  the shortened  $\rm (6, 3, 3)$  Hamming code is not perfect, so a single-error coset leader  $\underline{s}_{\mu}$  cannot be found for all possible  $\underline{e}_{\mu}$.
error coset leader  $\underline{s}_{\mu}$  cannot be found for all possible  $\underline{e}_{\mu}$ .
 
 
 
 
 
  
  
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 +
<u>Hints:</u>
 +
* The exercise refers to the chapter&nbsp; [[Channel_Coding/The_Basics_of_Product_Codes| "Basic Product Codes"]]&nbsp; and is intended as a supplement to&nbsp; [[Aufgaben:Exercise_4.7:_Product_Code_Decoding|$\text{Exercise 4.7}$]].
 +
 +
* Similar task settings were covered in&nbsp; [[Aufgaben:Exercise_1.11:_Syndrome_Decoding| $\text{Exercise 1.11}$]]&nbsp; and&nbsp; [[Aufgaben:Exercise_1.11Z:_Syndrome_Decoding_again|$\text{Exercise 1.11Z}$]]&nbsp; from chapter&nbsp; [[Channel_Coding/Decoding_of_Linear_Block_Codes|"Decoding Linear Block Codes"]].
  
 +
* The relationship between generator matrix&nbsp; $\mathbf{G}$&nbsp; and parity-check matrix&nbsp; $\mathbf{H}$&nbsp; of systematic codes is given in chapter&nbsp; [[Channel_Coding/General_Description_of_Linear_Block_Codes|"General Description of Linear Block Codes"]].
  
Hints:
 
* The exercise refers to the chapter&nbsp; [[Channel_Coding/The_Basics_of_Product_Codes| "Basic Product Codes"]]&nbsp; and is intended as a supplement to&nbsp; [[Aufgaben:Exercise_4.7:_Product_Code_Decoding| "Exercise 4.7"]]&nbsp;.
 
* Similar exercises were covered in the&nbsp; [[Aufgaben:Exercise_1.11:_Syndrome_Decoding| "Exercise 1.11"]]&nbsp; and the&nbsp; [[Aufgaben:Exercise_1.11Z:_Syndrome_Decoding_again| "Exercise 1.11Z"]]&nbsp; chapter&nbsp; [[Channel_Coding/Decoding_of_Linear_Block_Codes|"Decoding Linear Block Codes"]]&nbsp;.
 
* The relationship between generator matrix&nbsp; $\mathbf{G}$&nbsp; and parity-check matrix&nbsp; $\mathbf{H}$&nbsp; of systematic codes is given in chapter&nbsp; [[Channel_Coding/General_Description_of_Linear_Block_Codes|"General Description of Linear Block Codes"]]&nbsp;.
 
  
  
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===Questions===
 
===Questions===
 
<quiz display=simple>
 
<quiz display=simple>
{The received word be&nbsp; $\underline{y} = (0, \, 1, \, 1,\, 0, \, 1, \, 0)$, the syndrome&nbsp; $\underline{s} = (0, \, 1, \, 1)$. For which code word&nbsp; $\underline{x}$&nbsp; of&nbsp; $\mathcal{C}_1$&nbsp; does the syndrome decoder decide?
+
{The received word be&nbsp; $\underline{y} = (0, \, 1, \, 1,\, 0, \, 1, \, 0)$,&nbsp; the syndrome&nbsp; $\underline{s} = (0, \, 1, \, 1)$.&nbsp; For which code word&nbsp; $\underline{x}$&nbsp; of&nbsp; $\mathcal{C}_1$&nbsp; does the syndrome decoder decide?
 
|type="()"}
 
|type="()"}
- The most likely codeword is&nbsp; $\ \underline{x} = (1, \, 1, \, 1, \, 0, \, 1, \, 1, \, 0)$.
+
- The most likely code word is&nbsp; $\ \underline{x} = (1, \, 1, \, 1, \, 0, \, 1, \, 1, \, 0)$.
+ The most likely codeword is&nbsp; $\ \underline{x} = (0, \, 1, \, 0, \, 0, \, 1, \, 1, \, 0)$.
+
+ The most likely code word is&nbsp; $\ \underline{x} = (0, \, 1, \, 0, \, 0, \, 1, \, 1, \, 0)$.
- The most likely codeword is&nbsp; $\ \underline{x} = (0, \, 1, \, 0, \, 0, \, 1, \, 1, \, 1)$.
+
- The most likely code word is&nbsp; $\ \underline{x} = (0, \, 1, \, 0, \, 0, \, 1, \, 1, \, 1)$.
  
 
{What statements hold for the parity-check matrix&nbsp; $\mathbf{H}$&nbsp; of the truncated code&nbsp; $\mathcal{C}_2$?
 
{What statements hold for the parity-check matrix&nbsp; $\mathbf{H}$&nbsp; of the truncated code&nbsp; $\mathcal{C}_2$?
 
|type="[]"}
 
|type="[]"}
- This is a&nbsp; $4 &times 6$&ndash;matrix.
+
- This is a&nbsp; $4 &times 6$&nbsp; matrix.
+ The first row of this matrix is: &nbsp;$\ 110100$.
+
+ The first row of this matrix is&nbsp; "$110100$".
+ The second row of this matrix is: &nbsp;$\ 101010$.
+
+ The second row of this matrix is&nbsp; "$101010$".
+ The third row of this matrix is: &nbsp;$\ 011001$.
+
+ The third row of this matrix is&nbsp; "$011001$".
  
 
{What syndrome&nbsp; $\underline{s}$&nbsp; results for the error pattern&nbsp; $\underline{e} = (0, \, 0, \, 0, \, 0, \, 0, \, 0)$?
 
{What syndrome&nbsp; $\underline{s}$&nbsp; results for the error pattern&nbsp; $\underline{e} = (0, \, 0, \, 0, \, 0, \, 0, \, 0)$?
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===Solution===
 
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''&nbsp; Correct is <u>proposed solution 2</u>:
+
'''(1)'''&nbsp; Correct is the&nbsp; <u>proposed solution 2</u>:
*From the [[Aufgaben:Exercise_4.7Z: _Principle_of_Syndrome_Decoding| "Syndrome table"]] on the information page &ndash; valid for the $\rm (7, \ 4, \ 3)$&ndash;Hamming code &ndash; it can be read that the syndrome $\underline{s} = \underline{s}_3 = (0, \, 1, \, 1)$ corresponds to the error pattern $\underline{e} = (0, \, 0, \, 1, \, 0, \, 0, \, 0, \, 0)$. Thus the code word
+
*From the&nbsp; [[Aufgaben:Exercise_4.7Z: _Principle_of_Syndrome_Decoding| "syndrome table"]]&nbsp; on the information page &ndash; valid for the&nbsp; $\rm (7, 4, 3)$&nbsp; Hamming code &ndash; it can be read that the syndrome &nbsp; $\underline{s} = \underline{s}_3 = (0, \, 1, \, 1)$&nbsp; corresponds to the error pattern &nbsp; $\underline{e} = (0, \, 0, \, 1, \, 0, \, 0, \, 0, \, 0)$. Thus the code word
 
:$$\underline{x} = \underline{y} \hspace{0.15cm}+ \hspace{0.15cm}  \underline{y} = (0, 1, 1, 0, 1, 1, 0)  \hspace{0.15cm}+ \hspace{0.15cm}(0, 0, 1, 0, 0, 0, 0)
 
:$$\underline{x} = \underline{y} \hspace{0.15cm}+ \hspace{0.15cm}  \underline{y} = (0, 1, 1, 0, 1, 1, 0)  \hspace{0.15cm}+ \hspace{0.15cm}(0, 0, 1, 0, 0, 0, 0)
 
\hspace{0.15cm}= \hspace{0.15cm}(0, 1, 0, 0, 1, 1, 0)$$
 
\hspace{0.15cm}= \hspace{0.15cm}(0, 1, 0, 0, 1, 1, 0)$$
  
most likely and the syndrome decoder will output this as the result.
+
is most likely and the syndrome decoder will output this as the result.
  
  
  
'''(2)'''&nbsp; Correct are <u>solutions 2, 3, and 4</u>:
+
'''(2)'''&nbsp; Correct are the&nbsp; <u>solutions 2, 3, and 4</u>:
*The parity-check matrix $\mathbf{H}$ of the truncated $\rm (6, \ 3)$&ndash;Hamming code $C_2$ has $m = n - k = 3$ rows and $n$ columns. Consequently, it is a $3 &times 6$&ndash;matrix &nbsp; &#8658; &nbsp; statement 1 is false.
+
*The parity-check matrix&nbsp; $\mathbf{H}$&nbsp; of the truncated&nbsp; $\rm (6, 3)$&nbsp; Hamming code&nbsp; $C_2$&nbsp; has&nbsp; $m = n - k = 3$&nbsp; rows and&nbsp; $n$&nbsp; columns.&nbsp;  
  
 +
*Consequently,&nbsp; it is a&nbsp; $3 &times 6$&nbsp; matrix &nbsp; &#8658; &nbsp; statement 1 is false.
  
*Since $\mathcal{C}_2$ is also a systematic code, the generator matrix $\mathbf{G}$ can be represented in the following form:
+
*Since&nbsp; $\mathcal{C}_2$&nbsp; is also a systematic code,&nbsp; the generator matrix&nbsp; $\mathbf{G}$&nbsp; can be represented&nbsp; in the following form:
 
:$${ \boldsymbol{\rm G}}  
 
:$${ \boldsymbol{\rm G}}  
 
=  \begin{pmatrix}
 
=  \begin{pmatrix}
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\hspace{0.05cm}.$$
 
\hspace{0.05cm}.$$
  
*Here $\mathbf{I}_3$ denotes a $3 &times 3$ diagonal matrix typical of the systematic code.
+
*Here&nbsp; $\mathbf{I}_3$&nbsp; denotes a&nbsp; $3 &times 3$&nbsp; diagonal matrix typical of the systematic code.
  
*Proposed solutions 2, 3, and 4 are therefore correct:
+
*<u>Proposed solutions 2, 3, and 4</u>&nbsp; are therefore correct:
:* Row 1: &nbsp; $\ 110100$,
+
:* Row 1: &nbsp; $110100$,
:* Row 2: &nbsp; $\ 101010$,
+
:* Row 2: &nbsp; $101010$,
:* row 3: &nbsp; $\ 011001$.
+
:* Row 3: &nbsp; $011001$.
  
  
'''(3)'''&nbsp; Correct is <u>proposed solution 1</u>:
+
'''(3)'''&nbsp; Correct is the&nbsp; <u>proposed solution 1</u>:
*According to the statements in the chapter [[Channel_Coding/Decoding_of_Linear_Block_Codes| "Decoding of Linear Block Codes"]], $\underline{s} = \underline{e} \cdot \mathbf{H}^{\rm T}$ can be written.  
+
*According to the statements in the chapter&nbsp; [[Channel_Coding/Decoding_of_Linear_Block_Codes| "Decoding of Linear Block Codes"]] &nbsp; &rArr; &nbsp;  $\underline{s} = \underline{e} \cdot \mathbf{H}^{\rm T}$&nbsp; can be written.
*Thus, for the error-free case &nbsp; &#8658; &nbsp; $\underline{e} = (0, \, 0, \, 0, \, 0, \, 0, \, 0)$:
+
 +
*Thus,&nbsp; for the error-free case &nbsp; &#8658; &nbsp; $\underline{e} = (0, \, 0, \, 0, \, 0, \, 0, \, 0)$:
 
:$$\underline{s}= \left ( 0, \hspace{0.03cm} 0, \hspace{0.03cm}0, \hspace{0.03cm}0, \hspace{0.03cm}0, \hspace{0.03cm}0 \right ) \cdot
 
:$$\underline{s}= \left ( 0, \hspace{0.03cm} 0, \hspace{0.03cm}0, \hspace{0.03cm}0, \hspace{0.03cm}0, \hspace{0.03cm}0 \right ) \cdot
 
   \begin{pmatrix}
 
   \begin{pmatrix}
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'''(4)'''&nbsp; <u>All statements</u> are true, as can be seen from the sample solution to the last subtask:  
+
'''(4)'''&nbsp; <u>All statements</u>&nbsp; are true,&nbsp; as can be seen from the sample solution to the last subtask:  
*The rows of the transposed parity-check matrix, read from top to bottom, give the respective syndromes for the error patterns $\underline{e} = (1, \, 0, \, 0, \, 0, \, 0, \, 0), \hspace{0.05cm} \text{ ... } \hspace{0.05cm} , \ \underline{e} = (0, \, 0, \, 0, \, 0, \, 0, \, 1)$.
+
*The rows of the transposed parity-check matrix,&nbsp; read from top to bottom,&nbsp; give the respective syndromes for the error patterns $\underline{e} = (1, \, 0, \, 0, \, 0, \, 0, \, 0), \hspace{0.05cm} \text{ ... } \hspace{0.05cm} , \ \underline{e} = (0, \, 0, \, 0, \, 0, \, 0, \, 1)$.
  
  
  
'''(5)'''&nbsp; Correct are <u>solutions 2, 3, and 4</u>:
+
'''(5)'''&nbsp; Correct are the&nbsp; <u>solutions 2, 3, and 4</u>:
*The first statement is false because the first two rows of the transposed parity-check matrix  $\mathbf{H}^{\rm T}$ summed $(1, \, 1, \, 0) + (1, \, 0, \, 1) = (0, \, 1, \, 1) = \underline{s_3} &ne; \underline{s}_7$ results in.
+
*The first statement is false because the sum of the first two rows of the transposed parity-check matrix results in &nbsp; $\mathbf{H}^{\rm T}$ summed $(1, \, 1, \, 0) + (1, \, 0, \, 1) = (0, \, 1, \, 1) = \underline{s_3} &ne; \underline{s}_7$.
*Statements 2, 3 and 4, on the other hand, are correct:
+
*The statements 2, 3 and 4&nbsp;are correct:
 
:* First and last row: $\ (1, \, 1, \, 0) + (0, \, 0, \, 1) = (1, \, 1, \, 1) = \underline{s}_7$,
 
:* First and last row: $\ (1, \, 1, \, 0) + (0, \, 0, \, 1) = (1, \, 1, \, 1) = \underline{s}_7$,
 
:* second and fifth row: $\ (1, \, 0, \, 1) + (0, \, 1, \, 0) = (1, \, 1, \, 1) = \underline{s}_7$,
 
:* second and fifth row: $\ (1, \, 0, \, 1) + (0, \, 1, \, 0) = (1, \, 1, \, 1) = \underline{s}_7$,
:* The sum over all rows also gives $\underline{s}_7$, since there are exactly three ones in each matrix column.
+
:* The sum over all rows also gives&nbsp;  $\underline{s}_7$,&nbsp;  since there are exactly three&nbsp; "ones"&nbsp;  in each matrix column.
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  

Latest revision as of 16:53, 22 December 2022

Syndrome table for code  $\mathcal{C}_1$

The syndrome decoding was already treated in detail in the chapter  "Decoding of Linear Block Codes"

With all Hamming codes,  which are as well known perfect,  this gives a decoding result as good as with the  $($generally$)$ clearly more complicated maximum likelihood decoding.

For syndrome decoding one proceeds as follows:

  • One forms the syndrome from the received vector  $\underline{y}$  of length  $n$  and the parity-check matrix  $\mathbf{H}$:
$$\underline{s} = \underline{y} \cdot { \boldsymbol{\rm H}}^{\rm T} \in {\rm GF}(2^m) \hspace{0.05cm}, \hspace{0.5cm}{\rm Note\hspace{-0.10cm}:} \hspace{0.15cm}m = n-k \hspace{0.05cm}. $$
  • The received word  $\underline{y} = \underline{x} \ {\rm (code\:word)} + \underline{e} \ {\rm (error\:vector)}$  is not necessarily an element of  ${\rm GF}(2^m)$,  but certainly an element of  ${\rm GF}(2^n)$  and it holds because of   $\underline{x} \cdot \mathbf{H}^{\rm T} = \underline{0}$   equally:
$$\underline{s} = \underline{e} \cdot { \boldsymbol{\rm H}}^{\rm T}\hspace{0.05cm}. $$
  • Many error patterns  $\underline{e}$  lead to the same syndrome  $\underline{s}$. One now groups those error patterns with the same syndrome  $\underline{s}_{\mu}$  to the  "coset  ${\it \Psi}_{\mu}$".
  • The  "coset leader"  $\underline{e}_{\mu}$  is the error vector that has the lowest Hamming weight within the class  ${\it \Psi}_{\mu}$  and is accordingly the most probable.


The table above shows the list of the class leaders  $\underline{e}_{\mu}$  for each  $\underline{s}_{\mu}$  in the Hamming code  $\rm HC \ (7, 4, 3)$. This table is needed for the subtask  (1).

A similar table is to be created for the truncated Hamming code  $\rm HC \ (6, 3, 3)$.  This has already been used in the  $\text{Exercise 4.6}$  and the  $\text{Exercise 4.6Z}$  and is given by its generator matrix:

$${ \boldsymbol{\rm G}} = \begin{pmatrix} 1 &0 &0 &1 &1 &0 \\ 0 &1 &0 &1 &0 &1 \\ 0 &0 &1 &0 &1 &1 \end{pmatrix} \hspace{0.05cm}.$$

Unlike the original  $\rm (7, 4, 3)$  Hamming code,  the shortened  $\rm (6, 3, 3)$  Hamming code is not perfect, so a single-error coset leader  $\underline{s}_{\mu}$  cannot be found for all possible  $\underline{e}_{\mu}$.




Hints:



Questions

1

The received word be  $\underline{y} = (0, \, 1, \, 1,\, 0, \, 1, \, 0)$,  the syndrome  $\underline{s} = (0, \, 1, \, 1)$.  For which code word  $\underline{x}$  of  $\mathcal{C}_1$  does the syndrome decoder decide?

The most likely code word is  $\ \underline{x} = (1, \, 1, \, 1, \, 0, \, 1, \, 1, \, 0)$.
The most likely code word is  $\ \underline{x} = (0, \, 1, \, 0, \, 0, \, 1, \, 1, \, 0)$.
The most likely code word is  $\ \underline{x} = (0, \, 1, \, 0, \, 0, \, 1, \, 1, \, 1)$.

2

What statements hold for the parity-check matrix  $\mathbf{H}$  of the truncated code  $\mathcal{C}_2$?

This is a  $4 × 6$  matrix.
The first row of this matrix is  "$110100$".
The second row of this matrix is  "$101010$".
The third row of this matrix is  "$011001$".

3

What syndrome  $\underline{s}$  results for the error pattern  $\underline{e} = (0, \, 0, \, 0, \, 0, \, 0, \, 0)$?

$\underline{e} = (0, \, 0, \, 0, \, 0, \, 0, \, 0) \ \Rightarrow \ \underline{s} = \underline{s}_0 = (0, \, 0, \, 0)$,
$\underline{e} = (0, \, 0, \, 0, \, 0, \, 0, \, 0) \ \Rightarrow \ \underline{s} = \underline{s}_1 = (0, \, 0, \, 1)$,
$\underline{e} = (0, \, 0, \, 0, \, 0, \, 0, \, 0) \ \Rightarrow \ \underline{s} = \underline{s}_7 = (1, \, 1, \, 1)$.

4

Which of the following statements are true regarding single-error patterns?

single-error pattern   $\underline{e} = (1, \, 0, \, 0, \, 0, \, 0, \, 0)$   ⇒   syndrome $\underline{s}_6 = (1, \, 1, \, 0)$,
single-error pattern   $\underline{e} = (0, \, 1, \, 0, \, 0, \, 0, \, 0)$   ⇒   syndrome $\underline{s}_5 = (1, \, 0, \, 1)$,
single-error pattern   $\underline{e} = (0, \, 0, \, 1, \, 0, \, 0, \, 0)$   ⇒   syndrome $\underline{s}_3 = (0, \, 1, \, 1)$,
single-error pattern   $\underline{e} = (0, \, 0, \, 0, \, 1, \, 0, \, 0)$   ⇒   syndrome $\underline{s}_4 = (1, \, 0, \, 0)$,
single-error pattern   $\underline{e} = (0, \, 0, \, 0, \, 0, \, 1, \, 0)$   ⇒   syndrome $\underline{s}_2 = (0, \, 1, \, 0)$,
single-error pattern   $\underline{e} = (0, \, 0, \, 0, \, 0, \, 0, \, 1)$   ⇒   syndrome $\underline{s}_1 = (0, \, 0, \, 1)$,

5

Which of the following error patterns lead to the syndrome  $\underline{s}_7 = (1, \, 1, \, 1)$?

$\underline{e} = (1, \, 1, \, 0, \, 0, \, 0, \, 0)$,
$\underline{e} = (1, \, 0, \, 0, \, 0, \, 0, \, 1)$,
$\underline{e} = (0, \, 1, \, 0, \, 0, \, 1, \, 0)$,
$\underline{e} = (1, \, 1, \, 1, \, 1, \, 1, \, 1)$.


Solution

(1)  Correct is the  proposed solution 2:

  • From the  "syndrome table"  on the information page – valid for the  $\rm (7, 4, 3)$  Hamming code – it can be read that the syndrome   $\underline{s} = \underline{s}_3 = (0, \, 1, \, 1)$  corresponds to the error pattern   $\underline{e} = (0, \, 0, \, 1, \, 0, \, 0, \, 0, \, 0)$. Thus the code word
$$\underline{x} = \underline{y} \hspace{0.15cm}+ \hspace{0.15cm} \underline{y} = (0, 1, 1, 0, 1, 1, 0) \hspace{0.15cm}+ \hspace{0.15cm}(0, 0, 1, 0, 0, 0, 0) \hspace{0.15cm}= \hspace{0.15cm}(0, 1, 0, 0, 1, 1, 0)$$

is most likely and the syndrome decoder will output this as the result.


(2)  Correct are the  solutions 2, 3, and 4:

  • The parity-check matrix  $\mathbf{H}$  of the truncated  $\rm (6, 3)$  Hamming code  $C_2$  has  $m = n - k = 3$  rows and  $n$  columns. 
  • Consequently,  it is a  $3 × 6$  matrix   ⇒   statement 1 is false.
  • Since  $\mathcal{C}_2$  is also a systematic code,  the generator matrix  $\mathbf{G}$  can be represented  in the following form:
$${ \boldsymbol{\rm G}} = \begin{pmatrix} 1 &0 &0 &1 &1 &0 \\ 0 &1 &0 &1 &0 &1 \\ 0 &0 &1 &0 &1 &1 \end{pmatrix} = \left ( { \boldsymbol{\rm I}}_3 ; \hspace{0.15cm} { \boldsymbol{\rm P}} \right ) \hspace{0.5cm}{\rm mit }\hspace{0.5cm} { \boldsymbol{\rm P}} = \begin{pmatrix} 1 &1 &0 \\ 1 &0 &1 \\ 0 &1 &1 \end{pmatrix} \hspace{0.05cm}.$$
  • So it can be written for the parity-check matrix:
$${ \boldsymbol{\rm H}} = \left ( { \boldsymbol{\rm P}}^{\rm T} ; \hspace{0.15cm} { \boldsymbol{\rm I}}_3 \right ) = \begin{pmatrix} 1 &1 &0 &1 &0 &0\\ 1 &0 &1 &0 &1 &0\\ 0 &1 &1 &0 &0 &1 \end{pmatrix} \hspace{0.05cm}.$$
  • Here  $\mathbf{I}_3$  denotes a  $3 × 3$  diagonal matrix typical of the systematic code.
  • Proposed solutions 2, 3, and 4  are therefore correct:
  • Row 1:   $110100$,
  • Row 2:   $101010$,
  • Row 3:   $011001$.


(3)  Correct is the  proposed solution 1:

  • Thus,  for the error-free case   ⇒   $\underline{e} = (0, \, 0, \, 0, \, 0, \, 0, \, 0)$:
$$\underline{s}= \left ( 0, \hspace{0.03cm} 0, \hspace{0.03cm}0, \hspace{0.03cm}0, \hspace{0.03cm}0, \hspace{0.03cm}0 \right ) \cdot \begin{pmatrix} 1 &1 &0 \\ 1 &0 &1 \\ 0 &1 &1 \\ 1 &0 &0 \\ 0 &1 &0 \\ 0 &0 &1 \end{pmatrix}= \left ( 0, \hspace{0.03cm} 0, \hspace{0.03cm}0 \right ) = \underline{s}_0.$$


(4)  All statements  are true,  as can be seen from the sample solution to the last subtask:

  • The rows of the transposed parity-check matrix,  read from top to bottom,  give the respective syndromes for the error patterns $\underline{e} = (1, \, 0, \, 0, \, 0, \, 0, \, 0), \hspace{0.05cm} \text{ ... } \hspace{0.05cm} , \ \underline{e} = (0, \, 0, \, 0, \, 0, \, 0, \, 1)$.


(5)  Correct are the  solutions 2, 3, and 4:

  • The first statement is false because the sum of the first two rows of the transposed parity-check matrix results in   $\mathbf{H}^{\rm T}$ summed $(1, \, 1, \, 0) + (1, \, 0, \, 1) = (0, \, 1, \, 1) = \underline{s_3} ≠ \underline{s}_7$.
  • The statements 2, 3 and 4 are correct:
  • First and last row: $\ (1, \, 1, \, 0) + (0, \, 0, \, 1) = (1, \, 1, \, 1) = \underline{s}_7$,
  • second and fifth row: $\ (1, \, 0, \, 1) + (0, \, 1, \, 0) = (1, \, 1, \, 1) = \underline{s}_7$,
  • The sum over all rows also gives  $\underline{s}_7$,  since there are exactly three  "ones"  in each matrix column.