10,948 research outputs found
Optimal Thresholds for GMD Decoding with (L+1)/L-extended Bounded Distance Decoders
We investigate threshold-based multi-trial decoding of concatenated codes
with an inner Maximum-Likelihood decoder and an outer error/erasure
(L+1)/L-extended Bounded Distance decoder, i.e. a decoder which corrects e
errors and t erasures if e(L+1)/L + t <= d - 1, where d is the minimum distance
of the outer code and L is a positive integer. This is a generalization of
Forney's GMD decoding, which was considered only for L = 1, i.e. outer Bounded
Minimum Distance decoding. One important example for (L+1)/L-extended Bounded
Distance decoders is decoding of L-Interleaved Reed-Solomon codes. Our main
contribution is a threshold location formula, which allows to optimally erase
unreliable inner decoding results, for a given number of decoding trials and
parameter L. Thereby, the term optimal means that the residual codeword error
probability of the concatenated code is minimized. We give an estimation of
this probability for any number of decoding trials.Comment: Accepted for the 2010 IEEE International Symposium on Information
Theory, Austin, TX, USA, June 13 - 18, 2010. 5 pages, 2 figure
On the Construction and Decoding of Concatenated Polar Codes
A scheme for concatenating the recently invented polar codes with interleaved
block codes is considered. By concatenating binary polar codes with interleaved
Reed-Solomon codes, we prove that the proposed concatenation scheme captures
the capacity-achieving property of polar codes, while having a significantly
better error-decay rate. We show that for any , and total frame
length , the parameters of the scheme can be set such that the frame error
probability is less than , while the scheme is still
capacity achieving. This improves upon 2^{-N^{0.5-\eps}}, the frame error
probability of Arikan's polar codes. We also propose decoding algorithms for
concatenated polar codes, which significantly improve the error-rate
performance at finite block lengths while preserving the low decoding
complexity
Successive Cancellation Decoding of Single Parity-Check Product Codes
We introduce successive cancellation (SC) decoding of product codes (PCs)
with single parity-check (SPC) component codes. Recursive formulas are derived,
which resemble the SC decoding algorithm of polar codes. We analyze the error
probability of SPC-PCs over the binary erasure channel under SC decoding. A
bridge with the analysis of PCs introduced by Elias in 1954 is also
established. Furthermore, bounds on the block error probability under SC
decoding are provided, and compared to the bounds under the original decoding
algorithm proposed by Elias. It is shown that SC decoding of SPC-PCs achieves a
lower block error probability than Elias' decoding
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