Iterative decoding for cascaded LDPC and TCM coding
At a receiver side, to enhance the performance of concatenated LDPC and TCM coding, an iterative decoding between TCM decoder and LDPC decoder enables improvement in the reliability of received LLRs of each symbol after each iteration. A SOVA output of the TCM is used for LDPC decoding, and then the updated LLRs from LDPC decoder are further looped back to the TCM decoder for the next iteration. In such a manner, the decoding performance could be significantly improved after just several iterations.
1. A method for iterative decoding of a communications signal comprising the steps of:
i) decoding an input signal using a soft output Viterbi algorithm, the input signal being a concatenated low-density parity-check LDPC and TCM coded signal;
ii) de-interleaving output symbols from step i) for making errors in the decoding evenly distributed and statistically independent for improving error correction performance of subsequent LDPC decoding;
iii) LDPC decoding output from step ii), the decoding being initialized with Log-likelihood ratios LLRs output from step i);
iv) employing a soft quadrature amplitude modulator symbol estimator on output from step iii) for providing a likelihood of recovered symbols which can be used for further TCM decoding; and
v) ineterleaving the output from step iv) for putting estimated symbols back into an original position before sending it back to step i) if needed;
wherein with the soft-QAM symbol estimating of iv) and converged LLRs from the step i) decoding, the TCM decoder is enabled to achieve increased symbol detection with accurate LLRs in the next iteration.
2. The method of claim 1 , wherein sufficient coding gain is achievable with less than or equal to 3 iterations of steps i)-v).
3. The method of claim 1 , wherein step iii) comprises using a sum product algorithm (SPA) that could be used for decoding the LDPC codewords with multiple iterations.
4. The method of claim 1 , wherein step iii) comprises converged bit LLRs in the LDPC decoding to have been looped back to the soft-QAM symbol estimator and used for next-iteration TCM and LDPC decoding.
5. The method of claim 1 , wherein the soft-QAM symbol estimating calculates a probability of the each symbol based on the LLRs outputs from the LDPC decoder using
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λ i is the LLRs of the bit b i , s n is the QAM symbol with N constellation points, and (s n,1 , s n,2 , . . . stands for the bit mapping of the N-QAM, c=log 2 N representing c bits per symbol.
6. A non-transitory storage medium configured with instructions to be implemented by a computer for carrying out the following steps:
i) decoding an input signal using a soft output Viterbi algorithm, the input signal being a concatenated low-density parity-check LDPC and TCM coded signal;
ii) de-interleaving output symbols from step i) for making errors in the decoding evenly distributed and statistically independent for improving error correction performance of subsequent LDPC decoding;
iii) LDPC decoding output from step ii), the decoding being initialized with Log-likelihood ratios LLRs output from step i);
iv) employing a soft quadrature amplitude modulator symbol estimator on output from step iii) for providing a likelihood of recovered symbols which can be used for further TCM decoding; and
v) ineterleaving the output from step iv) for putting estimated symbols back into an original position before sending it back to step i) if needed;
wherein the soft-QAM symbol estimating of iv) and converged LLRs from the step i) decoding, the TCM decoder is enabled to achieve increased symbol detection with increased accurate LLRs in the next iteration.
7. The non-transitory storage medium of claim 6 , wherein sufficient coding gain is achievable with less than or equal to 3 iterations of steps i)-v).
8. The non-transitory storage medium of claim 6 , wherein step iii) comprises using a sum product algorithm (SPA) that could be used for decoding the LDPC codewords with multiple iterations.
9. The non-transitory storage medium of claim 6 , wherein step iii) comprises converged bit LLRs in the LDPC decoding to have been looped back to the soft-QAM symbol estimator and used for next-iteration TCM and LDPC decoding.
10. The non-transitory storage medium of claim 6 , wherein the soft-QAM symbol estimating calculates a probability of the each symbol based on the LLRs outputs from the LDPC decoder using
x
^
qam
=
∑
n
=
1
N
s
n
P
(
x
qam
=
s
n
)
=
∑
n
=
1
N
s
n
∏
i
=
1
c
P
(
b
i
=
s
n
,
i
)
where
P
(
b
i
=
0
)
=
1
ⅇ
-
λ
i
+
1
;
P
(
b
i
=
1
)
=
1
ⅇ
λ
i
+
1
,
λ i is the LLRs of the bit b i , s n is the QAM symbol with N constellation points, and (s n,1 , s n,2 , . . . stands for the bit mapping of the N-QAM, c=log 2 N representing c bits per symbol.