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Efficient Linear Programming Decoding of HDPC Codes
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DOI：10.1109/TCOMM.2011.122110.090729.png)
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Abstract
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We propose several improvements for Linear Programming (LP) decoding algorithms for High Density Parity Check (HDPC) codes. First, we use the automorphism groups of a code to create parity check matrix diversity and to generate valid cuts from redundant parity checks. Second, we propose an efficient mixed integer decoder utilizing the branch and bound method. We further enhance the proposed decoders by removing inactive constraints and by adapting the parity check matrix prior to decoding according to the channel observations. Based on simulation results the proposed decoders achieve near-ML performance with reasonable complexity.
Keywords:
Adaptive LP decoding
automorphism groups
BCH codes
belief propagation
branch and bound
linear programming
LP relaxation
pseudocodewords
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8.3
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1.2W
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3.6W
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