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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.
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29 Jun 2007TL;DR: In this article, an audio decoder provides a combination of decoding components including components implementing base band decoding, spectral peak decoding, frequency extension decoding and channel extension decoding techniques, and a bitstream syntax scheme to permit the various decoding components to extract the appropriate parameters for their respective decoding technique.
Abstract: An audio decoder provides a combination of decoding components including components implementing base band decoding, spectral peak decoding, frequency extension decoding and channel extension decoding techniques. The audio decoder decodes a compressed bitstream structured by a bitstream syntax scheme to permit the various decoding components to extract the appropriate parameters for their respective decoding technique.
116 citations
TL;DR: The performance of the convolutional codes is analyzed for the two modulation techniques and a new metric is developed for soft decision decoding of DAPSK modulated signals.
Abstract: The multilevel modulation techniques of 64-quadrature amplitude modulation (QAM) and 64-differential amplitude and phase-shift keying (DAPSK) have been proposed in combination with the orthogonal frequency-division multiplexing (OFDM) scheme for digital terrestrial video broadcasting (DTVB). With this system a data rate of 34 Mb/s can be transmitted over an 8-MHz radio channel. A comparison of these modulation methods in the uncoded case has been presented by Engels and Rohling (see European Trans. Telecommun., vol.6, p.633-40, 1995). The channel coding scheme proposed for DTVB by Schafer (see Proc. Int. Broadcasting Convention, Amsterdam, The Netherlands, p.79-84, 1995) consists of an inner convolutional code concatenated with an outer Reed-Solomon (RS) code. In this paper the performance of the convolutional codes is analyzed for the two modulation techniques. This analysis includes soft decision Viterbi (1971) decoding of the convolutional code. For soft decision decoding of DAPSK modulated signals a new metric is developed.
116 citations
TL;DR: This work proposes PA codes as a class of prospective codes with good performance, low decoding complexity, regular structure, and flexible rate adaptivity for all rates above 1/2, and shows that these codes provide performance similar to turbo codes but with significantly less decoding complexity and with a lower error floor.
Abstract: We propose a novel class of provably good codes which are a serial concatenation of a single-parity-check (SPC)-based product code, an interleaver, and a rate-1 recursive convolutional code. The proposed codes, termed product accumulate (PA) codes, are linear time encodable and linear time decodable. We show that the product code by itself does not have a positive threshold, but a PA code can provide arbitrarily low bit-error rate (BER) under both maximum-likelihood (ML) decoding and iterative decoding. Two message-passing decoding algorithms are proposed and it is shown that a particular update schedule for these message-passing algorithms is equivalent to conventional turbo decoding of the serial concatenated code, but with significantly lower complexity. Tight upper bounds on the ML performance using Divsalar's (1999) simple bound and thresholds under density evolution (DE) show that these codes are capable of performance within a few tenths of a decibel away from the Shannon limit. Simulation results confirm these claims and show that these codes provide performance similar to turbo codes but with significantly less decoding complexity and with a lower error floor. Hence, we propose PA codes as a class of prospective codes with good performance, low decoding complexity, regular structure, and flexible rate adaptivity for all rates above 1/2.
115 citations
TL;DR: An efficient maximum-likelihood decoding algorithm for decoding low-density parity-check codes over the binary-erasure channel (BEC) and the computational complexity of the proposed algorithm is analyzed.
Abstract: We propose an efficient maximum-likelihood (ML) decoding algorithm for decoding low-density parity-check (LDPC) codes over the binary-erasure channel (BEC). We also analyze the computational complexity of the proposed algorithm.
115 citations
TL;DR: An efficient general GMD decoding scheme for linear block codes in the framework of error-correcting pairs is derived and it is shown that it can find all relevant error-erasure-locating functions with complexity O(o/ sub 1/nd), where o/sub 1/ is the size of the first nongap in the function space associated with the code.
Abstract: Generalized minimum-distance (GMD) decoding is a standard soft-decoding method for block codes. We derive an efficient general GMD decoding scheme for linear block codes in the framework of error-correcting pairs. Special attention is paid to Reed-Solomon (RS) codes and one-point algebraic-geometry (AG) codes. For RS codes of length n and minimum Hamming distance d the GMD decoding complexity turns out to be in the order O(nd), where the complexity is counted as the number of multiplications in the field of concern. For AG codes the GMD decoding complexity is highly dependent on the curve in consideration. It is shown that we can find all relevant error-erasure-locating functions with complexity O(o/sub 1/nd), where o/sub 1/ is the size of the first nongap in the function space associated with the code. A full GMD decoding procedure for a one-point AG code can be performed with complexity O(dn/sup 2/).
114 citations