Difference between revisions of "Aufgaben:Exercise 4.09: Recursive Systematic Convolutional Codes"
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'''(3)''' Correct are <u>the proposed solutions 1 and 2</u>: | '''(3)''' Correct are <u>the proposed solutions 1 and 2</u>: | ||
*Between the impulse response g_ and the D–transfer function G(D) there is the relation according to the first proposed solution: | *Between the impulse response g_ and the D–transfer function G(D) there is the relation according to the first proposed solution: | ||
− | $$\underline{g}= (\hspace{-0.05cm}1\hspace{-0.05cm}, | + | :$$\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}1\hspace{-0.05cm}, | \hspace{-0.05cm}1\hspace{-0.05cm}, | ||
Line 113: | Line 113: | ||
\hspace{-0.05cm}1\hspace{-0.05cm}, | \hspace{-0.05cm}1\hspace{-0.05cm}, | ||
\hspace{-0.05cm}1\hspace{-0.05cm}, | \hspace{-0.05cm}1\hspace{-0.05cm}, | ||
− | ... ) \hspace{0.3cm} \circ\!\!-\!\!\!-^{\hspace{-0.25cm}D}\!\!\!-\!\!\bullet | + | ... ) \hspace{0.3cm} \circ\!\!-\!\!\!-^{\hspace{-0.25cm}D}\!\!\!-\!\!\bullet \hspace{0.3cm} |
− | 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 + | + | 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 + \text{...} .$$ |
*Let us now examine the second proposal: | *Let us now examine the second proposal: |
Revision as of 16:12, 14 December 2022
In 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 RSC stands for "recursive systematic convolutional".
The transfer function matrix of an RSC convolutional code can be specified as follows:
- G(D)=[1,G(2)(D)/G(1)(D)].
Otherwise, exactly the same conditions apply here as in Exercise 4.8. We refer again to the following theory pages:
- "Systematic convolutional codes"
- "Representation in the state transition diagram"
- "Definition of the free distance"
- "GF(2) description forms of a digital filter"
- "Application of the D–transform to rate 1/n convolution encoders"
- "Filter structure with fractional–rational transfer function"
In the state transition diagram, two arrows go from each state. The label is "ui|x(1)ix(2)i". For a systematic code, this involves:
- The first code bit is identical to the information bit: x(1)i=ui∈{0,1}.
- The second code bit is the parity-check bit: x(2)i=pi∈{0,1}.
Hints:
- The exercise refers to the chapter "Basics of Turbo Codes".
- The following vectorial quantities are used in the questions for this exercise:
- the information sequence: u_=(u1,u2,...),
- the parity-check sequence: p_=(p1,p2,...),
- the impulse response: g_=(g1,g2,...); this is equal to the parity sequence p_ for u_=(1,0,0,...).
Questions
Solution
- S0→S1→S3→S2→S1→S3→S2→S1→S3→...
- For each transition, the first code symbol x(1)i is equal to the information bit ui and the code symbol x(2)i indicates the parity-check bit pi.
- This gives the result corresponding to solution proposition 1:
- p_=(1,1,1,0,1,1,0,1,1,...)=g_.
- For any RSC code, the impulse response g_ is infinite in length and becomes periodic at some point, in this example with period P=3 and "0,1,1".
(2) The graph shows the solution of this exercise according to the equation p_=u_T⋅G.
- Here the generator matrix 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 g_ and the D–transfer function G(D) there is the relation according to the first proposed solution:
- g_=(1,1,1,0,1,1,0,1,1,...)∘−−D−∙G(D)=1+D+D2+D4+D5+D7+D8+....
- Let us now examine the second proposal:
- G(D)=1+D21+D+D2⇒G(D)⋅[1+D+D2]=1+D2.
- The following calculation shows that this equation is indeed true:
- (1+D+D2+D4+D5+D7+D8+...)⋅(1+D+D2)=
- =1+D+D2+D4+D5+D7+D8+D10+...
- +D+D2+D3+D5+D6+D8+D9+...
- +D2+D3+D4+D6+D7+D9+D10+...
- =1+D2_.
- But since equation (2) is true, the last equation must be false.
(4) Correct is only the proposed solution 1:
- From u_=(1,1,1) follows U(D)=1+D+D2. Thus also holds:
- P(D)=U(D)⋅G(D)=(1+D+D2)⋅1+D21+D+D2=1+D2⇒p_=(1,0,1,0,0,...).
- If the variables ui and gi were real-valued, the (discrete) convolution p_=u_∗g_ would always lead to a broadening ⇒ p_ in this case would be broader than u_ and also broader than g_.
- On the other hand, for ui∈GF(2) and gi∈GF(2) it may (but need not) happen that even with unbounded u_ or for unbounded g_ the convolution product p_=u_∗g_ is bounded.
- The result is finally checked according to the equation p_=u_T⋅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 S0→S0→S1→S2→S0→S0→....
- But the associated code sequence x_ is now " 00 11 10 11 00 ...".
- This gives the free distance to dF =5_.
- In contrast, in the non-recursive code (exercise 4.8), the free distance was dF=3.