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arxiv: cs/0602088 · v1 · submitted 2006-02-26 · 💻 cs.IT · math.IT

Towards Low-Complexity Linear-Programming Decoding

classification 💻 cs.IT math.IT
keywords algorithmdecodingconnectedduallinear-programmingmethodsmin-sumrules
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We consider linear-programming (LP) decoding of low-density parity-check (LDPC) codes. While it is clear that one can use any general-purpose LP solver to solve the LP that appears in the decoding problem, we argue in this paper that the LP at hand is equipped with a lot of structure that one should take advantage of. Towards this goal, we study the dual LP and show how coordinate-ascent methods lead to very simple update rules that are tightly connected to the min-sum algorithm. Moreover, replacing minima in the formula of the dual LP with soft-minima one obtains update rules that are tightly connected to the sum-product algorithm. This shows that LP solvers with complexity similar to the min-sum algorithm and the sum-product algorithm are feasible. Finally, we also discuss some sub-gradient-based methods.

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