Topic
Sequential decoding
About: Sequential decoding is a research topic. Over the lifetime, 8667 publications have been published within this topic receiving 204271 citations.
Papers published on a yearly basis
Papers
More filters
••
TL;DR: In this article, a generalized successive cancellation flip (SCFlip) decoding of polar codes is proposed, where one or several positions are flipped from the standard SC decoding to correct the trajectory of the SC decoding.
Abstract: This paper proposes a generalization of the recently introduced successive cancellation flip (SCFlip) decoding of polar codes, characterized by a number of extra decoding attempts, where one or several positions are flipped from the standard SC decoding. To make such an approach effective, we first introduce the concept of higher order bit flips and propose a new metric to determine the bit flips that are more likely to correct the trajectory of the SC decoding. We then propose a generalized SCFlip decoding algorithm, referred to as dynamic-SCFlip (D-SCFlip), which dynamically builds a list of candidate bit flips, while guaranteeing that the next attempt has the highest probability of success among the remaining ones. Simulation results show that D-SCFlip is an effective alternative to SC-list decoding of polar codes, by providing very good error correcting performance, with an average computation complexity close to the one of the SC decoder.
103 citations
••
30 Jun 2002TL;DR: With a proper choice of the initial p, the proposed improved bit-flipping (BF) algorithm achieves gain not only in performance, but also in average decoding time for signal-to-noise ratio (SNR) values of interest with respect to p = 1.
Abstract: In this correspondence, a new method for improving hard-decision bit-flipping decoding of low-density parity-check (LDPC) codes is presented. Bits with a number of unsatisfied check sums larger than a predetermined threshold are flipped with a probability p /spl les/ 1 which is independent of the code considered. The probability p is incremented during decoding according to some rule. With a proper choice of the initial p, the proposed improved bit-flipping (BF) algorithm achieves gain not only in performance, but also in average decoding time for signal-to-noise ratio (SNR) values of interest with respect to p = 1.
103 citations
••
27 Jun 1994
TL;DR: The simple soft output viterbi algorithm (SOVA) meets all the requirements for iterative decoding if an a priori term is added and surprisingly good performance is achieved for the Gaussian and Rayleigh channel.
Abstract: Iterative decoding of two dimensional systematic convolutional codes has been termed "turbo"-(de)coding. It is shown that the simple soft output viterbi algorithm (SOVA) meets all the requirements for iterative decoding if an a priori term is added. With simple 4 and 16 state codes surprisingly good performance is achieved for the Gaussian and Rayleigh channel with a very small degradation relative to the complicated MAP algorithm. >
103 citations
••
TL;DR: In this paper, a new algorithm based on unrolling the decoding tree of the polar code was proposed to improve the speed of list decoding by an order of magnitude when implemented in software.
Abstract: Polar codes asymptotically achieve the symmetric capacity of memoryless channels, yet their error-correcting performance under successive-cancellation (SC) decoding for short and moderate length codes is worse than that of other modern codes such as low-density parity-check (LDPC) codes. Of the many methods to improve the error-correction performance of polar codes, list decoding yields the best results, especially when the polar code is concatenated with a cyclic redundancy check (CRC). List decoding involves exploring several decoding paths with SC decoding, and therefore tends to be slower than SC decoding itself, by an order of magnitude in practical implementations. In this paper, we present a new algorithm based on unrolling the decoding tree of the code that improves the speed of list decoding by an order of magnitude when implemented in software. Furthermore, we show that for software-defined radio applications, our proposed algorithm is faster than the fastest software implementations of LDPC decoders in the literature while offering comparable error-correction performance at similar or shorter code lengths.
103 citations
••
TL;DR: An adaptive decoding algorithm for convolutional codes, which is a modification of the Viterbi algorithm (VA), which yields nearly the same error performance as the VA while requiring a substantially smaller average number of computations.
Abstract: In this paper, an adaptive decoding algorithm for convolutional codes, which is a modification of the Viterbi algorithm (VA) is presented For a given code, the proposed algorithm yields nearly the same error performance as the VA while requiring a substantially smaller average number of computations Unlike most of the other suboptimum algorithms, this algorithm is self-synchronizing If the transmitted path is discarded, the adaptive Viterbi algorithm (AVA) can recover the state corresponding to the transmitted path after a few trellis depths Using computer simulations over hard and soft 3-bit quantized additive white Gaussian noise channels, it is shown that codes with a constraint length K up to 11 can be used to improve the bit-error performance over the VA with K=7 while maintaining a similar average number of computations Although a small variability of the computational effort is present with our algorithm, this variability is exponentially distributed, leading to a modest size of the input buffer and, hence, a small probability of overflow
103 citations