Journal ArticleDOI
Fast Converging ADMM-Penalized Algorithm for LDPC Decoding
TLDR
A formulation of the ADMM decoding algorithm with modified computation scheduling is proposed that increases the error correction performance of the decoding algorithm and reduces the average computation complexity of the decode process thanks to a faster convergence.Abstract:
The alternate direction method of multipliers (ADMM) approach has been recently considered for LDPC decoding. It has been approved to enhance the error rate performance compared with conventional message passing (MP) techniques in both the waterfall and error floor regions at the cost of a higher computation complexity. In this letter, a formulation of the ADMM decoding algorithm with modified computation scheduling is proposed. It increases the error correction performance of the decoding algorithm and reduces the average computation complexity of the decoding process thanks to a faster convergence. Simulation results show that this modified scheduling speeds up the decoding procedure with regards to the ADMM initial formulation while enhancing the error correction performance. This decoding speed-up is further improved when the proposed scheduling is teamed with a recent complexity reduction method detailed in Wei et al. IEEE Commun. Lett. , 2015.read more
Citations
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Journal ArticleDOI
An Iterative Check Polytope Projection Algorithm for ADMM-Based LP Decoding of LDPC Codes
Haoyuan Wei,Amir H. Banihashemi +1 more
TL;DR: This letter proposes an iterative algorithm, without sorting operation, for projection onto the parity-check polytope, which has a worst case complexity linear in the input dimension compared with the super-linear complexity of existing algorithms.
Journal ArticleDOI
Efficient ADMM Decoding of LDPC Codes Using Lookup Tables
TL;DR: Simulation results show that for both the regular and irregular LDPC codes, the ADMM decoding using LUT-based projection can substantially reduce the decoding time while maintaining the error rate performance at a comparatively large memory cost.
Journal ArticleDOI
Decoding Binary Linear Codes Using Penalty Dual Decomposition Method
TL;DR: This letter utilizes the penalty dual decomposition (PDD) framework and develops a novel PDD decoding algorithm for binary linear codes that shows great error rate performance at both low and high signal-to-noise ratios.
Journal ArticleDOI
Reduced Complexity Node-Wise Scheduling of ADMM Decoding for LDPC Codes
TL;DR: This letter investigates the node-wise scheduling for ADMM decoders, named NS-ADMM, and proposes a reduced-complexity method by avoiding Euclidean projections involved in the calculation of message residuals, which converges much faster than the flooding and layered scheduling while keeping a lower complexity.
Journal ArticleDOI
Improved Penalty Functions of ADMM Penalized Decoder for LDPC Codes
TL;DR: Improved piecewise penalty functions for ADMM penalized decoder are designed that can punish pseudocodewords more quickly and thus increase the decoding speed.
References
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Journal ArticleDOI
Reduced complexity iterative decoding of low-density parity check codes based on belief propagation
TL;DR: Two simplified versions of the belief propagation algorithm for fast iterative decoding of low-density parity check codes on the additive white Gaussian noise channel are proposed, which greatly simplifies the decoding complexity of belief propagation.
Proceedings ArticleDOI
A reduced complexity decoder architecture via layered decoding of LDPC codes
TL;DR: The previously devised irregular partitioned permutation LDPC codes have a construction that easily accommodates a layered decoding and it is shown that the decoding performance is improved by a factor of two in the number of iterations required.
Dissertation
Decoding error-correcting codes via linear programming
Jon Feldman,David R. Karger +1 more
TL;DR: This thesis investigates the application of linear programming (LP) relaxation to the problem of decoding an error-correcting code, and provides specific LP decoders for two major families of codes: turbo codes and low-density parity-check codes.
Posted Content
Decomposition Methods for Large Scale LP Decoding
TL;DR: This paper draws on decomposition methods from optimization theory, specifically the alternating direction method of multipliers (ADMM), to develop efficient distributed algorithms for LP decoding, and develops an efficient algorithm for Euclidean norm projection onto the parity polytope.
Journal ArticleDOI
Decomposition Methods for Large Scale LP Decoding
TL;DR: In this paper, a two-slice characterization of the parity polytope is presented, which simplifies the representation of points in the parity space and allows the decoding of large-scale error-correcting codes efficiently.