Difference between revisions of "Aufgaben:Exercise 4.7Z: Principle of Syndrome Decoding"
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− | [[File: | + | [[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"]]. | The syndrome decoding was already treated in detail in the chapter [[Channel_Coding/Decoding_of_Linear_Block_Codes| "Decoding of Linear Block Codes"]]. | ||
Latest revision as of 15:53, 22 December 2022
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:
- The exercise refers to the chapter "Basic Product Codes" and is intended as a supplement to $\text{Exercise 4.7}$.
- Similar task settings were covered in $\text{Exercise 1.11}$ and $\text{Exercise 1.11Z}$ from chapter "Decoding Linear Block Codes".
- The relationship between generator matrix $\mathbf{G}$ and parity-check matrix $\mathbf{H}$ of systematic codes is given in chapter "General Description of Linear Block Codes".
Questions
Solution
- 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:
- According to the statements in the chapter "Decoding of Linear Block Codes" ⇒ $\underline{s} = \underline{e} \cdot \mathbf{H}^{\rm T}$ can be written.
- 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.