Low-density parity-check (LDPC) code[1][2]


Also known as Gallager codes. Binary or \(q\)-ary linear code with a sparse parity-check matrix. More precisely, a member of an infinite family of \([n,k,d]\) codes for which the number of nonzero entries in each row and column of the parity-check matrix are both bounded by a constant as \(n\to\infty\). An LDPC code is \((j,k)\)-regular if the parity-check matrix has a fixed number of \(j\) nonzero entries in each row and \(k\) entries in each column; otherwise, the LDPC code is irregular. The dual of an LDPC code has a sparse generator matrix and is called an LDGM code.

A parity check is performed by taking the inner product of a row of the parity-check matrix with a codeword that has been affected by a noise channel. A parity check yields either zero (no error) or one (error) for binary codes, while yielding zero (no error) or a nonzero field element (error) for \(q\)-ary codes. Despite the fact that there is more than one nonzero outcome, \(q\)-ary linear codes with sparse parity-check matrices are also called LDPC codes.


With high probability, random LDPC codes have constant distance [2].


Achieve capacity on the binary symmetric channel under maximum-likelihood decoding [3][1][4]. Some LDPC codes achieve capacity for smaller block lengths under belief-propagation decoding [5]. Random LDPC codes achieve list-decoding capacity [6].


Almost linear-time encoder based on transforming parity-check matrix into upper triangular form [7].


Message-passing algorithm called belief propagation (BP) [2][8].Linear programming [9].


5G NR cellular communication for the traffic channel [10].WiMAX (IEEE 802.16e) [11].Satellite transmission of digital television [12].


See Kaiserslautern database [13] for explicit representatives of several classes of LDPC codes, including \(q\)-ary, WiMAX, multi-edge, and spatially-coupled.See pretty-good-codes database [14] for explicit representatives and benchmarking.See Ref. [15] for a review of LDPC codes circa 2005.Codes have been benchmarked using AFF3CT toolbox [16].See book [17] for an introduction to LDPC codes, belief-propagation decoding, and connections to statistical mechanics.





R. Gallager, “Low-density parity-check codes”, IEEE Transactions on Information Theory 8, 21 (1962). DOI
R. Gallagher, Low-density parity check codes. 1963. PhD thesis, MIT Cambridge, MA.
D. J. C. MacKay, “Good error-correcting codes based on very sparse matrices”, IEEE Transactions on Information Theory 45, 399 (1999). DOI
Venkatesan Guruswami, “Iterative Decoding of Low-Density Parity Check Codes (A Survey)”. cs/0610022
Shrinivas Kudekar, Tom Richardson, and Ruediger Urbanke, “Spatially Coupled Ensembles Universally Achieve Capacity under Belief Propagation”. 1201.2999
Jonathan Mosheiff et al., “LDPC Codes Achieve List Decoding Capacity”. 1909.06430
T. J. Richardson and R. L. Urbanke, “Efficient encoding of low-density parity-check codes”, IEEE Transactions on Information Theory 47, 638 (2001). DOI
S. Lin and D. J. Costello, Error Control Coding, 2nd ed. Englewood Cliffs, NJ: Prentice-Hall, 2004.
J. Feldman, “LP Decoding”, Encyclopedia of Algorithms 1177 (2016). DOI
M. V. Patil, S. Pawar, and Z. Saquib, “Coding Techniques for 5G Networks: A Review”, 2020 3rd International Conference on Communication System, Computing and IT Applications (CSCITA) (2020). DOI
LDPC coding for OFDMA PHY. 802.16REVe Sponsor Ballot Recirculation comment, July 2004. IEEE C802.16e04/141r2
R. Purnamasari, H. Wijanto, and I. Hidayat, “Design and implementation of LDPC(Low Density Parity Check) coding technique on FPGA (Field Programmable Gate Array) for DVB-S2 (Digital Video Broadcasting-Satellite)”, 2014 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology (2014). DOI
Michael Helmling, Stefan Scholl, Florian Gensheimer, Tobias Dietz, Kira Kraft, Stefan Ruzika, and Norbert Wehn. Database of Channel Codes and ML Simulation Results. URL, 2022.
G. Liva, F. Steiner. “pretty-good-codes.org: Online library of good channel codes”, URL: http://pretty-good-codes.org/
A. Shokrollahi, “LDPC Codes: An Introduction”, Coding, Cryptography and Combinatorics 85 (2004). DOI
A. Cassagne et al., “AFF3CT: A Fast Forward Error Correction Toolbox!”, SoftwareX 10, 100345 (2019). DOI
M. Mézard and A. Montanari, Information, Physics, and Computation (Oxford University PressOxford, 2009). DOI
I. Dinur, M. Sudan, and A. Wigderson, “Robust Local Testability of Tensor Products of LDPC Codes”, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques 304 (2006). DOI
E. Ben-Sasson and M. Viderman, “Tensor Products of Weakly Smooth Codes Are Robust”, Lecture Notes in Computer Science 290 (2008). DOI
A. Shokrollahi, “Raptor codes”, IEEE Transactions on Information Theory 52, 2551 (2006). DOI
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“Low-density parity-check (LDPC) code”, The Error Correction Zoo (V. V. Albert & P. Faist, eds.), 2022. https://errorcorrectionzoo.org/c/ldpc
@incollection{eczoo_ldpc, title={Low-density parity-check (LDPC) code}, booktitle={The Error Correction Zoo}, year={2022}, editor={Albert, Victor V. and Faist, Philippe}, url={https://errorcorrectionzoo.org/c/ldpc} }
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“Low-density parity-check (LDPC) code”, The Error Correction Zoo (V. V. Albert & P. Faist, eds.), 2022. https://errorcorrectionzoo.org/c/ldpc

Github: https://github.com/errorcorrectionzoo/eczoo_data/tree/main/codes/classical/properties/ldpc.yml.