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Sequential decoding

About: Sequential decoding is a research topic. Over the lifetime, 8667 publications have been published within this topic receiving 204271 citations.


Papers
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Proceedings ArticleDOI
06 Jul 2001
TL;DR: This paper compares the speed and output quality of a traditional stack-based decoding algorithm with two new decoders: a fast greedy decoder and a slow but optimal decoder that treats decoding as an integer-programming optimization problem.
Abstract: A good decoding algorithm is critical to the success of any statistical machine translation system. The decoder's job is to find the translation that is most likely according to set of previously learned parameters (and a formula for combining them). Since the space of possible translations is extremely large, typical decoding algorithms are only able to examine a portion of it, thus risking to miss good solutions. In this paper, we compare the speed and output quality of a traditional stack-based decoding algorithm with two new decoders: a fast greedy decoder and a slow but optimal decoder that treats decoding as an integer-programming optimization problem.

300 citations

Journal ArticleDOI
TL;DR: A modification of the Fincke-Pohst (sphere decoding) algorithm to estimate the maximum a posteriori probability of the received symbol sequence is proposed and, over a wide range of rates and signal-to-noise ratios, has polynomial-time complexity.
Abstract: In recent years, soft iterative decoding techniques have been shown to greatly improve the bit error rate performance of various communication systems. For multiantenna systems employing space-time codes, however, it is not clear what is the best way to obtain the soft information required of the iterative scheme with low complexity. In this paper, we propose a modification of the Fincke-Pohst (sphere decoding) algorithm to estimate the maximum a posteriori probability of the received symbol sequence. The new algorithm solves a nonlinear integer least squares problem and, over a wide range of rates and signal-to-noise ratios, has polynomial-time complexity. Performance of the algorithm, combined with convolutional, turbo, and low-density parity check codes, is demonstrated on several multiantenna channels. The results for systems that employ space-time modulation schemes seem to indicate that the best performing schemes are those that support the highest mutual information between the transmitted and received signals, rather than the best diversity gain.

298 citations

Book ChapterDOI
15 Apr 2012
TL;DR: The ball collision technique of Bernstein, Lange and Peters was used to reduce the complexity of Stern's information set decoding algorithm to 20.0556n by as mentioned in this paper, and this bound was improved by May, Meurer and Thomae.
Abstract: Decoding random linear codes is a well studied problem with many applications in complexity theory and cryptography. The security of almost all coding and LPN/LWE-based schemes relies on the assumption that it is hard to decode random linear codes. Recently, there has been progress in improving the running time of the best decoding algorithms for binary random codes. The ball collision technique of Bernstein, Lange and Peters lowered the complexity of Stern's information set decoding algorithm to 20.0556n. Using representations this bound was improved to 20.0537n by May, Meurer and Thomae. We show how to further increase the number of representations and propose a new information set decoding algorithm with running time 20.0494n.

295 citations

Journal ArticleDOI
TL;DR: The method is to define an idealized model, called the classic bursty channel, toward which most burst-correcting schemes are explicitly or implicitly aimed, and to bound the best possible performance on this channel to exhibit classes of schemes which are asymptotically optimum.
Abstract: The purpose of this paper is to organize and clarify the work of the past decade on burst-correcting codes. Our method is, first, to define an idealized model, called the classic bursty channel, toward which most burst-correcting schemes are explicitly or implicitly aimed; next, to bound the best possible performance on this channel; and, finally, to exhibit classes of schemes which are asymptotically optimum and serve as archetypes of the burstcorrecting codes actually in use. In this light we survey and categorize previous work on burst-correcting codes. Finally, we discuss qualitatively the ways in which real channels fail to satisfy the assumptions of the classic bursty channel, and the effects of such failures on the various types of burst-correcting schemes. We conclude by comparing forward-error-correction to the popular alternative of automatic repeat-request (ARQ).

295 citations

Journal ArticleDOI
TL;DR: Simulations using the 1MT-2000/3GPP parameters demonstrate that this method gives /spl sim/0.2 to 0.4 dB performance gain compared to the standard max-log-MAP algorithm.
Abstract: Decoding turbo codes with the max-log-MAP algorithm is a good compromise between performance and complexity. The decoding quality of the max-log-MAP decoder is improved by using a scaling factor within the extrinsic calculation. Simulations using the 1MT-2000/3GPP parameters demonstrate that this method gives /spl sim/0.2 to 0.4 dB performance gain compared to the standard max-log-MAP algorithm.

294 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202351
2022112
202124
202026
201922
201832