scispace - formally typeset
Journal ArticleDOI

An Iterative Decoding Algorithm with Backtracking to Lower the Error-Floors of LDPC Codes

TLDR
A technique is proposed to break trapping sets while decoding to lower the error-floor, which has moderate complexity overhead and is applicable to any code without requiring a prior knowledge of the structure of its trapping sets.
Abstract
Error-floors are the main reason for excluding LDPC codes from applications requiring very low bit-error rate. They are attributed to a particular structure in the codes' Tanner graphs, known as trapping sets, which traps the message-passing algorithms commonly used to decode LDPC codes, and prevents decoding from converging to the correct codeword. A technique is proposed to break trapping sets while decoding. Based on decoding results leading to a decoding failure, some bits are identified in a previous iteration and flipped and decoding is restarted. This backtracking may enable the decoder to get out of the trapped state. A semi-analytical method is also proposed to predict the error-floor after backtracking. Simulation results indicate the effectiveness of the proposed technique in lowering the error-floor. The technique, which has moderate complexity overhead, is applicable to any code without requiring a prior knowledge of the structure of its trapping sets.

read more

Citations
More filters
Journal ArticleDOI

Cyclic and Quasi-Cyclic LDPC Codes on Constrained Parity-Check Matrices and Their Trapping Sets

TL;DR: Several classes of finite-geometry and finite-field cyclic and quasi-cyclic LDPC codes with large minimum distances are shown to have no harmful trapping sets of size smaller than their minimum distances, Consequently, their error-floor performances are dominated by theirminimum distances.
Patent

Flash channel with selective decoder likelihood dampening

TL;DR: In this article, an apparatus for reading a flash memory includes a read controller, a likelihood generator, a decoder, a data state storage, and a selective dampening controller to select at least one dampening candidate from among the likelihood values for which decoding failed, and provide the dampened likelihood values to the decoder for decoding.
MonographDOI

LDPC Code Designs, Constructions, and Unification

TL;DR: This self-contained text provides systematic coverage of LDPC codes and their construction techniques, unifying both algebraic- and graph-based approaches into a single theoretical framework (the superposition construction).
Journal ArticleDOI

Controlling the Error Floor in LDPC Decoding

TL;DR: The error floor of LDPC is revisited as an effect of dynamic message behavior in the so-called absorbing sets of the code and it is shown that if the signal growth in the absorbing sets is properly balanced by the growth of set-external messages, the error floor can be lowered to essentially arbitrarily low levels.
Patent

Read retry for non-volatile memories

TL;DR: In this paper, an apparatus for reading a non-volatile memory includes a tracking module that calculates means and variances of voltage level distributions in nonvolatile memories, and a likelihood generator that calculates at least one other reference voltage to be used when reading the nonvivo memory.
References
More filters
Book

Low-Density Parity-Check Codes

TL;DR: A simple but nonoptimum decoding scheme operating directly from the channel a posteriori probabilities is described and the probability of error using this decoder on a binary symmetric channel is shown to decrease at least exponentially with a root of the block length.
Journal ArticleDOI

Good error-correcting codes based on very sparse matrices

TL;DR: It is proved that sequences of codes exist which, when optimally decoded, achieve information rates up to the Shannon limit, and experimental results for binary-symmetric channels and Gaussian channels demonstrate that practical performance substantially better than that of standard convolutional and concatenated codes can be achieved.
Journal ArticleDOI

Regular and irregular progressive edge-growth tanner graphs

TL;DR: Simulation results show that the PEG algorithm is a powerful algorithm to generate good short-block-length LDPC codes.

Good error-correcting codes based on very sparse matrices (vol 45, pg 339, 1999)

Djc MacKay
TL;DR: It can be proved that, given an optimal decoder, Gallager's low density parity check codes asymptotically approach the Shannon limit.