Adaptive Cut Generation Algorithm for Improved Linear Programming Decoding of Binary Linear Codes

Linear programming (LP) decoding approximates maximum-likelihood (ML) decoding of a linear block code by relaxing the equivalent ML integer programming (IP) problem into a more easily solved LP problem. The LP problem is defined by a set of box constraints together with a set of linear inequalities...

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Bibliographic Details
Published in:	IEEE transactions on information theory Vol. 58; no. 10; pp. 6581 - 6594
Main Authors:	Xiaojie Zhang, Siegel, P. H.
Format:	Journal Article
Language:	English
Published:	New York, NY IEEE 01.10.2012 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithm design and analysis Algorithms Applied sciences Approximation Block codes Codes Coding theory Coding, codes Decoders Decoding Exact sciences and technology Inequalities Information theory Information, signal and communications theory Iterative decoding linear codes Linear programming linear programming (LP) decoding Low density parity check codes low-density parity-check (LDPC) codes Matrix Maximum likelihood decoding Maximum likelihood method maximum-likelihood (ML) decoding Parity pseudocodewords Signal and communications theory Simulation Telecommunications and information theory Vectors Performance evaluation Block code linear codes Adaptive algorithm Error estimation Error rate Iterative method maximum-likelihood (ML) decoding Binary code Adaptive method pseudocodewords Iterative decoding Linear code low-density parity-check (LDPC) codes Parity check codes Linear programming Maximum likelihood decoding Integer programming Necessary condition linear programming (LP) decoding Sufficient condition Simulation Hypercube Error correcting code Parity check
ISSN:	0018-9448, 1557-9654
Online Access:	Get full text
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