Sequential decoding

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

Code doping for triggering iterative decoding convergence

Abstract: The paper describes inner and outer code doping to enable iterative decoding of serially concatenated codes (SCC) which use inner rate one recursive convolutional codes of memory greater than one.

Decoding the Golay codes

Abstract: We introduce exceptionally simple decoding algorithms for the two extended Golay codes The algorithms are based on recent methods of Conway and Curtis of finding the unique blocks containing five points in either the (5,8,24) Steiner system or the (5,6,12) Steiner system These decoding methods are simple enough to enable decoding extended Golay codes by hand Both of the methods involve relations between the extended Golay codes and other self-dual codes Proofs are given explaining these relationships and why the decoding methods work The decoding algorithms are explained and illustrated with many examples [3 , chap 12] has facts about the Mathieu group and some details about decoding the Golay codes

Method, medium, and apparatus encoding and/or decoding an image using the same coding mode across components

Abstract: A method, medium, and apparatus encoding and/or decoding an image in order to increase encoding and decoding efficiency by performing binary-arithmetic coding/decoding on a binary value of a syntax element using a probability model having the same syntax element probability value for respective context index information of each of at least two image components.

A reconfigurable, power-efficient adaptive Viterbi decoder

Abstract: Error-correcting convolutional codes provide a proven mechanism to limit the effects of noise in digital data transmission. Although hardware implementations of decoding algorithms, such as the Viterbi algorithm, have shown good noise tolerance for error-correcting codes, these implementations require an exponential increase in very large scale integration area and power consumption to achieve increased decoding accuracy. To achieve reduced decoder power consumption, we have examined and implemented decoders based on the reduced-complexity adaptive Viterbi algorithm (AVA). Run-time dynamic reconfiguration is performed in response to varying communication channel-noise conditions to match minimized power consumption to required error-correction capabilities. Experimental calculations indicate that the use of dynamic reconfiguration leads to a 69% reduction in decoder power consumption over a nonreconfigurable field-programmable gate array implementation with no loss of decode accuracy.

Viterbi decoding apparatus and methods

Abstract: A received data decoding apparatus receives and decodes transmitted convolutional code data. The received data is formed of a first channel whose data rate is fixed and a second channel whose data rate is variable. The received data decoding apparatus includes a most likelihood decoder for decoding the received data on the basis of a Viterbi algorithm and a data rate decision unit for obtaining a predetermined data rate of the second channel determined according to a path metric amount which is a decoded output from the most likelihood decoder.