23 research outputs found
Efficient Linear Programming Decoding of HDPC Codes
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.Comment: Submitted to the IEEE Transactions on Communications, November 200
Fountain Codes under Maximum Likelihood Decoding
This dissertation focuses on fountain codes under maximum likelihood (ML)
decoding. First LT codes are considered under a practical and widely used ML
decoding algorithm known as inactivation decoding. Different analysis
techniques are presented to characterize the decoding complexity. Next an upper
bound to the probability of decoding failure of Raptor codes under ML decoding
is provided. Then, the distance properties of an ensemble of fixed-rate Raptor
codes with linear random outer codes are analyzed. Finally, a novel class of
fountain codes is presented, which consists of a parallel concatenation of a
block code with a linear random fountain code.Comment: PhD Thesi
Mathematical Programming Decoding of Binary Linear Codes: Theory and Algorithms
Mathematical programming is a branch of applied mathematics and has recently
been used to derive new decoding approaches, challenging established but often
heuristic algorithms based on iterative message passing. Concepts from
mathematical programming used in the context of decoding include linear,
integer, and nonlinear programming, network flows, notions of duality as well
as matroid and polyhedral theory. This survey article reviews and categorizes
decoding methods based on mathematical programming approaches for binary linear
codes over binary-input memoryless symmetric channels.Comment: 17 pages, submitted to the IEEE Transactions on Information Theory.
Published July 201