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Advances in Mathematics of Communications

On multi-trial Forney-Kovalev decoding of concatenated codes

Anas Chaaban, Vladimir R. Sidorenko, Christian Senger

Published Jan 1, 2014• 1 citation
Publisher

Abstract

A concatenated code $\mathcal{C} $ based on an inner code with Hamming distance $d^i$ and an outer code with Hamming distance $d^o$ is considered. An outer decoder that corrects $\varepsilon$ errors and $\theta$ erasures with high probability if $\lambda \varepsilon + \theta \le d^o - 1,$ where a real number $1<\lambda\le 2$ is the trade-off rate between errors and erasures for this decoder is used. In particular, an outer $l$-punctured RS code, i.e., a code over the field $\mathbb{F}_{q^{l }}$ of length $n^{o} < q$ with locators taken from the sub-field $\mathbb{F}_{q}$, where $l\in \{1,2,\ldots\}$ is considered. In this case, the trade-off is given by $\lambda=1+1/l$. An $m$-trial decoder, where after inner decoding, in each trial we erase an incremental number of symbols and decode using the outer decoder is proposed. The optimal erasing strategy and the error correcting radii of both fixed and adaptive erasing decoders are given. Our approach extends results of Forney and Kovalev (obtained for $\lambda=2$) to the whole given range of $\lambda$. For the fixed erasing strategy the error correcting radius approaches $\rho_F\approx\frac{d^i d^o}{2}(1-\frac{l^{-m}}{2})$ for large $d^o$. For the adaptive erasing strategy, the error correcting radius $\rho_A\approx\frac{d^i d^o}{2}(1-l^{-2m})$ quickly approaches $d^i d^o/2$ if $l$ or $m$ grows. The minimum number of trials required to reach an error correcting radius $d^i d^o/2$ is $m_A=\frac{1}{2}\left(\log_ld+1\right)$. This means that $2$ or $3$ trials are sufficient in many practical cases if $l>1$.

DOI
10.3934/amc.2014.8.1

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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 ε errors and τ erasures if ℓ+1/ ℓε+τ≤ do-1, where dois the minimum distance of the outer code and ℓ ∈ ℕ\{0}. 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.
For a concatenated coding scheme using a single inner code, a single outer code, and an optimal single-trial decoding strategy, we study the guaranteed error correction rate, i.e., the number of correctable errors per transmitted symbol. In particular, it is investigated whether the optimal guaranteed error correction rate can be achieved by finite length codes or only be approached by an infinite sequence of codes of increasing lengths. It is shown that optimizing the guaranteed error correction rate for a given inner or outer code does not necessarily mean pushing the code rate to zero. Furthermore, to optimize the guaranteed error correction rate over all inner and outer codes of fixed dimensions and alphabets, the code rate of one (but not both) of these two codes should be pushed to zero.
The error-correction capability and the performance of generalized minimum distance decod- ing based on threshold erasing is studied as a function of the number of decoding trials and of the allowable reliability values. Generalized Minimum Distance (GMD) decoding, as intro- duced by Forney (l), is a multitrial decoding algorithm that combines reliability information, represented by numbers in the closed interval (0,1), with algebraic decoding algorithms for error correction. In each trial, a fixed number of the most unreliable symbols in the received sequence is erased. If a cer- tain distance criterion is satisfied, Forney has shown that the transmitted codeword can be retrieved in at most (d/2) trials, where d is the Hamming distance of the code. In this work, we study a variation on Forney's scheme where, in each trial, symbols whose reliabilities are below a certain threshold are erased, and hence there is no need to sort the received symbols according to reliability values be- fore erasing as in Forney's GMD decoding. Furthermore, we consider limiting the allowable reliability values to the set R, = u~=mo/2'{1 - 2i/m}, where m = 1,2,3,. . .. This covers the simple cases of taking only hard decisions (m = l), allow- ing erasures (m = 2), or accommodating the full range (0,1) of reliability values as in Forney's GMD decoding (m + 00). Limiting the reliability values may be of importance since, in any digital implementation, the reliability values need to be quantized. Moreover, in some applications, e.g., GMD decod- ing of concatenated codes over discrete channels, the reliabil- ity values are discrete in nature (2). The maximum number of trials is kept as a parameter. Limiting the reliability values and the number of trials leads to the concept of reduced GMD decoding.
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High-rate concatenated quantum codes offer a promising pathway toward fault-tolerant quantum computation, yet designing efficient decoders that fully exploit their error-correction capability remains a significant challenge. In this work, we introduce a hard-decision decoder for concatenated quantum Hamming codes with time complexity polynomial in the block length. This decoder overcomes the limitations of conventional local decoding by leveraging higher-level syndrome information to revise lower-level recovery decisions -- a strategy we refer to as bidirectional decoding. For the concatenated [[15,7,3]][[15,7,3]][[15,7,3]] quantum Hamming code under independent bit-flip noise, the bidirectional decoder improves the threshold from approximately 1.56%1.56\%1.56% to 4.35%4.35\%4.35% compared with standard local decoding. Moreover, the decoder empirically preserves the full 3L3^{L}3L code-distance scaling for at least three levels of concatenation, resulting in substantially faster logical-error suppression than the 2L+12^{L+1}2L+1 scaling offered by local decoders. Our results can enhance the competitiveness of concatenated-code architectures for low-overhead fault-tolerant quantum computation.