Results 1 to 10 of about 1,096,634 (365)
Stochastic Iterative Decoders [PDF]
arXiv, 2005 This paper presents a stochastic algorithm for iterative error control decoding. We show that the stochastic decoding algorithm is an approximation of the sum-product algorithm. When the code's factor graph is a tree, as with trellises, the algorithm approaches maximum a-posteriori decoding.
Vincent Gaudet +3 more
arxiv +6 more sources
Erasure Codes with a Banded Structure for Hybrid Iterative-ML Decoding [PDF]
arXiv, 2009 This paper presents new FEC codes for the erasure channel, LDPC-Band, that have been designed so as to optimize a hybrid iterative-Maximum Likelihood (ML) decoding. Indeed, these codes feature simultaneously a sparse parity check matrix, which allows an efficient use of iterative LDPC decoding, and a generator matrix with a band structure, which allows
Alexandre Soro +3 more
arxiv +12 more sources
New Criteria for Iterative Decoding [PDF]
ICASSP, Taipei : Taiwan (2009), 2010 Iterative decoding was not originally introduced as the solution to an optimization problem rendering the analysis of its convergence very difficult. In this paper, we investigate the link between iterative decoding and classical optimization techniques.
Alberge, Florence +2 more
arxiv +10 more sources
An Iterative Joint Linear-Programming Decoding of LDPC Codes and Finite-State Channels [PDF]
, 2010 In this paper, we introduce an efficient iterative solver for the joint linear-programming (LP) decoding of low-density parity-check (LDPC) codes and finite-state channels (FSCs). In particular, we extend the approach of iterative approximate LP decoding, proposed by Vontobel and Koetter and explored by Burshtein, to this problem.
Kim, Byung-Hak, Pfister, Henry D.
arxiv +4 more sources
Design of Low-Latency Layered Normalized Minimum Sum Low-Density Parity-Check Decoding Based on Entropy Feature for NAND Flash-Memory Channel [PDF]
EntropyAs high-speed big-data communications impose new requirements on storage latency, low-density parity-check (LDPC) codes have become a widely used technology in flash-memory channels.
Yingge Li, Haihua Hu
doaj +2 more sources
Iterative Channel Equalization, Channel Decoding and Source Decoding [PDF]
2005 IEEE 61st Vehicular Technology Conference, 2005 The performance of soft source decoding is evaluated over dispersive AWGN channels. By employing source codes having error-correcting capabilities, such as reversible variable-length codes (RVLC) and variable-length error-correcting (VLEC) codes, the soft-in/soft-out (SISO) source decoder benefits from exchanging information with the MAP equalizer, and
Wang, J., Yang, L-L., Hanzo, L.
openaire +3 more sources
Iterative Decoding of Concatenated Codes: A Tutorial
EURASIP Journal on Advances in Signal Processing, 2005 The turbo decoding algorithm of a decade ago constituted a milestone in error-correction coding for digital communications, and has inspired extensions to generalized receiver topologies, including turbo equalization, turbo synchronization, and turbo ...
Phillip A. Regalia
doaj +4 more sources
Iterative Soft-Input Soft-Output Decoding of Reed–Solomon Codes by Adapting the Parity-Check Matrix [PDF]
, 2006 An iterative algorithm is presented for soft-input-soft-output (SISO) decoding of Reed-Solomon (RS) codes. The proposed iterative algorithm uses the sum product algorithm (SPA) in conjunction with a binary parity check matrix of the RS code.
Jiang Ji, Krishna R. Narayanan
openalex +7 more sources
Approaching capacity at high rates with iterative hard-decision decoding [PDF]
IEEE International Symposium on Information Theory. Proceedings, 2012 A variety of low-density parity-check (LDPC) ensembles have now been observed to approach capacity with message-passing decoding. However, all of them use soft (i.e., non-binary) messages and a posteriori probability (APP) decoding of their component ...
Yung-Yih Jian, H. Pfister, K. Narayanan
semanticscholar +4 more sources
Convergence of iterative decoding [PDF]
Electronics Letters, 1999 A novel method for visualising the convergence behaviour of iterative decoding schemes is proposed. Each constituent decoder is represented by a mutual information transfer characteristic which describes the flow of extrinsic information through the soft
S. Brink
semanticscholar +2 more sources