Exercise 4.09: Recursive Systematic Convolutional Codes

State transition diagram
of an RSC code

In $\text{Exercise 4.8}$ important properties of convolutional codes have already been derived from the state transition diagram, assuming a non-recursive filter structure.

Now a rate $1/2$ RSC code is treated in a similar manner. Here $\rm RSC$ stands for "recursive systematic convolutional".

The transfer function matrix of an RSC convolutional code can be specified as follows:

${\boldsymbol{\rm G}}(D) = \left [ 1\hspace{0.05cm},\hspace{0.3cm} G^{(2)}(D)/G^{(1)}(D) \right ] \hspace{0.05cm}.$

Otherwise, exactly the same conditions apply here as in Exercise 4.8. We refer again to the following theory pages:

In the state transition diagram, two arrows go from each state. The label is " $u_i \hspace{0.05cm}| \hspace{0.05cm} x_i^{(1)}x_i^{(2)}$ ". For a systematic code, this involves:

The first code bit is identical to the information bit: $\hspace{0.2cm} x_i^{(1)} = u_i ∈ \{0, \, 1\}$ .
The second code bit is the parity-check bit: $\hspace{0.2cm} x_i^{(2)} = p_i ∈ \{0, \, 1\}$ .

Hints:

The exercise refers to the chapter "Basics of Turbo Codes".
Similar exercises can be found in chapters 3.1 through 3.3.

The following vectorial quantities are used in the questions for this exercise:
- the information sequence: $\hspace{0.2cm} \underline{u} = (u_1, \, u_2, \text{...} \hspace{0.05cm} )$ ,
- the parity-check sequence: $\hspace{0.2cm} \underline{p} = (p_1, \, p_2, \text{...} \hspace{0.05cm})$ ,
- the impulse response: $\hspace{0.2cm} \underline{g} = (g_1, \, g_2, \text{...} \hspace{0.05cm} ); \hspace{0.2cm}$ this is equal to the parity sequence $\underline{p}$ for $\underline{u} = (1, \, 0, \, 0, \text{...} \hspace{0.05cm} )$ .

Questions

Solution

(1) Tracing the transitions in the state diagram for the sequence

$\underline{u} = (1, \, 0, \, 0, \, 0, \, 0, \, 0, \, 0, \, 0, \, 0)$ at the input, we get the path

$S_0 → S_1 → S_3 → S_2 → S_1 → S_3 → S_2 → S_1 → S_3 → \hspace{0.05cm}\text{...} \hspace{0.05cm}$

For each transition, the first code symbol $x_i^{(1)}$ is equal to the information bit $u_i$ and the code symbol $x_i^{(2)}$ indicates the parity-check bit $p_i$ .
This gives the result corresponding to solution proposition 1:

$\underline{p}= (\hspace{0.05cm}1\hspace{0.05cm}, \hspace{0.05cm}1\hspace{0.05cm}, \hspace{0.05cm}1\hspace{0.05cm}, \hspace{0.05cm} 0\hspace{0.05cm}, \hspace{0.05cm} 1\hspace{0.05cm}, \hspace{0.05cm} 1\hspace{0.05cm}, \hspace{0.05cm} 0\hspace{0.05cm}, \hspace{0.05cm} 1\hspace{0.05cm}, \hspace{0.05cm} 1\hspace{0.05cm},\hspace{0.05cm}\text{...} \hspace{0.05cm}) = \underline{g}\hspace{0.05cm}.$

For any RSC code, the impulse response $\underline{g}$ is infinite in length and becomes periodic at some point, in this example with period $P = 3$ and " $0, \, 1, \, 1$ ".

Clarification of

$\underline{p} = (1, \, 1, \, 0, \, 1)^{\rm T} \cdot \mathbf{G}$

(2) The graph shows the solution of this exercise according to the equation $\underline{p} = \underline{u}^{\rm T} \cdot \mathbf{G}$ .

Here the generator matrix $\mathbf{G}$ is infinitely extended downward and to the right.
The correct solution is proposal 2.

(3) Correct are the proposed solutions 1 and 2:

Between the impulse response $\underline{g}$ and the $D$ –transfer function $\mathbf{G}(D)$ there is the relation according to the first proposed solution:

$\underline{g}= (\hspace{-0.05cm}1\hspace{-0.05cm}, \hspace{-0.05cm}1\hspace{-0.05cm}, \hspace{-0.05cm}1\hspace{-0.05cm}, \hspace{-0.05cm}0\hspace{-0.05cm}, \hspace{-0.05cm}1\hspace{-0.05cm}, \hspace{-0.05cm}1\hspace{-0.05cm}, \hspace{-0.05cm}0\hspace{-0.05cm}, \hspace{-0.05cm}1\hspace{-0.05cm}, \hspace{-0.05cm}1\hspace{-0.05cm}, ... ) \quad \circ\!\!-\!\!\!-^{\hspace{-0.25cm}D}\!\!\!-\!\!\bullet\quad G(D) = 1\hspace{-0.05cm}+\hspace{-0.05cm} D\hspace{-0.05cm} +\hspace{-0.05cm} D^2\hspace{-0.05cm} +\hspace{-0.05cm} D^4 \hspace{-0.05cm}+\hspace{-0.05cm} D^5 \hspace{-0.05cm}+\hspace{-0.05cm} D^7 \hspace{-0.05cm}+\hspace{-0.05cm} D^8 + \hspace{0.05cm} \text{...} \hspace{0.05cm}.$

Let us now examine the second proposal:

$G(D) = \frac{1+ D^2}{1+ D + D^2} \hspace{0.3cm}\Rightarrow \hspace{0.3cm} G(D) \cdot [1+ D + D^2] = 1+ D^2 \hspace{0.05cm}.$

The following calculation shows that this equation is indeed true:

$(1+ D+ D^2+ D^4 +D^5 + D^7 + D^8 + \hspace{0.05cm} \text{...}) \cdot (1+ D+ D^2 ) =$

$=1+ D+ D^2\hspace{1.05cm} +D^4 + D^5 \hspace{1.05cm} +D^7 + D^8 \hspace{1.05cm} + D^{10}+ \hspace{0.05cm} \text{...}$

$+ \hspace{0.8cm}D+ D^2+D^3 \hspace{1.05cm}+ D^5 + D^6 \hspace{1.05cm} +D^8 + D^9 \hspace{1.25cm} +\hspace{0.05cm} \text{...}$

$+ \hspace{1.63cm} D^2+D^3+ D^4 \hspace{1.05cm}+ D^6 +D^7 \hspace{1.05cm}+ D^9 + D^{10} \hspace{0.12cm}+ \hspace{0.05cm} \text{...}$

$=\underline{1\hspace{0.72 cm}+ D^2} \hspace{0.05cm}.$

But since equation (2) is true, the last equation must be false.

(4) Correct is only the proposed solution 1:

From $\underline{u} = (1, \, 1, \, 1)$ follows $U(D) = 1 + D + D^2$ . Thus also holds:

$P(D) = U(D) \cdot G(D) = (1+D+D^2) \cdot \frac{1+D^2}{1+D+D^2}= 1+D^2\hspace{0.3cm} \Rightarrow\hspace{0.3cm} \underline{p}= (\hspace{0.05cm}1\hspace{0.05cm},\hspace{0.05cm} 0\hspace{0.05cm},\hspace{0.05cm} 1\hspace{0.05cm},\hspace{0.05cm} 0\hspace{0.05cm},\hspace{0.05cm} 0\hspace{0.05cm},\hspace{0.05cm}\text{...}\hspace{0.05cm})\hspace{0.05cm}.$

If the variables $u_i$ and $g_i$ were real-valued, the (discrete) convolution $\underline{p} = \underline{u} * \underline{g}$ would always lead to a broadening ⇒ $\underline{p}$ in this case would be broader than $\underline{u}$ and also broader than $\underline{g}$ .
On the other hand, for $u_i ∈ {\rm GF}(2)$ and $g_i ∈ {\rm GF}(2)$ it may (but need not) happen that even with unbounded $\underline{u}$ or for unbounded $\underline{g}$ the convolution product $\underline{p} = \underline{u} * \underline{g}$ is bounded.

Verdeutlichung von

$\underline{p} = (1, \, 1, \, 1, \, 0, \, ...)^{\rm T} \cdot \mathbf{G}$

The result is finally checked according to the equation $\underline{p} = \underline{u}^{\rm T} \cdot \mathbf{G}$ is checked.

(5) Following a similar procedure as in "Exercise A4.8, (4)", one can see:

The free distance is again determined by the path $S_0 → S_0 → S_1 → S_2 → S_0 → S_0 → \hspace{0.05cm}\text{...}\hspace{0.05cm}$ .
But the associated code sequence $\underline{x}$ is now " $00 \ 11 \ 10 \ 11 \ 00 \ ...$ ".
This gives the free distance to $d_{\rm F} \ \underline{= 5}$ .
In contrast, in the non-recursive code (exercise 4.8), the free distance was $d_{\rm F} = 3$ .

	$\underline{g} = (1, \, 1, \, 1, \, 0, \, 1, \, 1, \, 0, \, 1, \, 1, \text{...} \hspace{0.05cm})$ holds.
	$\underline{g} = (1, \, 0, \, 1, \, 0, \, 0, \, 0, \, 0, \, 0, \, 0, \text{...} \hspace{0.05cm})$ holds.

	$\underline{p} = (1, \, 0, \, 1, \, 0, \, 0, \, 0, \, 0, \, 0, \, 0, \, 0, \, 0, \, 0, \text{...} \hspace{0.05cm})$ holds.
	$\underline{p} = (1, \, 0, \, 0, \, 0, \, 0, \, 1, \, 1, \, 0, \, 1, \, 1, \, 0, \, 1, \text{...} \hspace{0.05cm})$ holds.
	With limited information sequence $\underline{u}$ is always also $\underline{p}$ limited.

	$G(D) = 1 + D + D^2 + D^4 + D^5 + D^7 + D^8 + \text{...} \hspace{0.05cm}$ holds.
	$G(D) = (1 + D^2)/(1 + D + D^2)$ holds.
	$G(D) = (1 + D + D^2)/(1 + D^2)$ holds.

	$\underline{p} = (1, \, 0, \, 1, \, 0, \, 0, \, 0, \, 0, \, 0, \, 0, \, 0, \, 0, \, 0, \text{...} \hspace{0.05cm})$ holds.
	$\underline{p} = (1, \, 0, \, 0, \, 0, \, 0, \, 1, \, 1, \, 0, \, 1, \, 1, \, 0, \, 1, \text{...} \hspace{0.05cm})$ holds.
	With unlimited impulse response $\underline{g}$ is always also $\underline{p}$ unlimited.