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List decoding

About: List decoding is a research topic. Over the lifetime, 7251 publications have been published within this topic receiving 151182 citations.


Papers
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Proceedings ArticleDOI
28 Jun 2009
TL;DR: This work presents a decoding algorithm called full rank decoding that extends the decodability of LT codes by using Wiedemann algorithm and reduces the overhead significantly in the cases of small number of input symbols yet preserves the simplicity of the original LT decoding process.
Abstract: LT codes provide an efficient way to transfer information over erasure channels. Past research has illustrated that LT codes can perform well for a large number of input symbols. However, it is shown that LT codes have poor performance when the number of input symbols is small. We notice that the poor performance is due to the design of the LT decoding process. In this respect, we present a decoding algorithm called full rank decoding that extends the decodability of LT codes by usingWiedemann algorithm.We provide a detailed mathematical analysis on the rank of the random coefficient matrix to evaluate the probability of successful decoding for our proposed algorithm. Our studies show that our proposed method reduces the overhead significantly in the cases of small number of input symbols yet preserves the simplicity of the original LT decoding process.

30 citations

Journal ArticleDOI
TL;DR: An improved bit-flipping decoding algorithm for high-rate finite-geometry low-density parity-check (FG-LDPC) codes is proposed and shows improvement in performance and reduction in decoding delay.
Abstract: In this letter, an improved bit-flipping decoding algorithm for high-rate finite-geometry low-density parity-check (FG-LDPC) codes is proposed. Both improvement in performance and reduction in decoding delay are observed by flipping multiple bits in each iteration. Our studies show that the proposed algorithm achieves an appealing tradeoff between performance and complexity for FG-LDPC codes.

30 citations

Proceedings ArticleDOI
TL;DR: A general upper bound on the list-decoding average error probability is derived on the fixed list-size regime, and an immediate byproduct of analysis in both regimes is the universality of the maximum mutual information list decoder in the error exponent sense.
Abstract: Some new results are derived concerning random coding error exponents and expurgated exponents for list decoding with a deterministic list size $L$. Two asymptotic regimes are considered, the fixed list-size regime, where $L$ is fixed independently of the block length $n$, and the exponential list-size, where $L$ grows exponentially with $n$. We first derive a general upper bound on the list-decoding average error probability, which is suitable for both regimes. This bound leads to more specific bounds in the two regimes. In the fixed list-size regime, the bound is related to known bounds and we establish its exponential tightness. In the exponential list-size regime, we establish the achievability of the well known sphere packing lower bound. Relations to guessing exponents are also provided. An immediate byproduct of our analysis in both regimes is the universality of the maximum mutual information (MMI) list decoder in the error exponent sense. Finally, we consider expurgated bounds at low rates, both using Gallager's approach and the Csiszar-Korner-Marton approach, which is, in general better (at least for $L=1$). The latter expurgated bound, which involves the notion of {\it multi-information}, is also modified to apply to continuous alphabet channels, and in particular, to the Gaussian memoryless channel, where the expression of the expurgated bound becomes quite explicit.

30 citations

Proceedings ArticleDOI
04 May 2014
TL;DR: A hardware architecture of the successive cancellation list decoder in the log-likelihood ratio domain is proposed which requires less irregular and smaller memories, and leads to 56% to 137% higher throughput per unit area than other recently proposed architectures.
Abstract: We present an LLR-based implementation of the successive cancellation list (SCL) decoder. To this end, we associate each decoding path with a metric which (i) is a monotone function of the path’s likelihood and (ii) can be computed efficiently from the channel LLRs. The LLR-based formulation leads to a more efficient hardware implementation of the decoder compared to the known log-likelihood based implementation. Synthesis results for an SCL decoder with block-length of N = 1024 and list sizes of L = 2 and L = 4 confirm that the LLR-based decoder has considerable area and operating frequency advantages in the orders of 50% and 30%, respectively.

30 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202384
2022153
202179
202078
201982
201894