Interior point decoding for linear vector channels based on convex optimization
Wadayama, T.
Nagoya Inst. of Technol., Nagoya;
This paper appears in: Information Theory, 2008. ISIT 2008. IEEE International Symposium on
Publication Date: 6-11 July 2008
On page(s): 1493-1497
Location: Toronto, ON,
ISBN: 978-1-4244-2256-2
INSPEC Accession Number: 10156124
Digital Object Identifier: 10.1109/ISIT.2008.4595236
Current Version Published: 2008-08-08
Abstract
In this paper, a novel decoding algorithm for low-density parity-check (LDPC) codes based on convex optimization is presented. The decoding algorithm, called interior point decoding, is designed for linear vector channels. The linear vector channels include many practically important channels such as inter symbol interference channels, partial response channels and MIMO channels. It is shown that the maximum likelihood decoding (MLD) rule for a linear vector channel can be relaxed to a convex optimization problem, which is called a relaxed MLD problem. Approximate variations of gradient descent and Newton methods are used to solve the convex optimization problem.
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