Journal ArticleDOI
Low-Latency Reweighted Belief Propagation Decoding for LDPC Codes
Jingjing Liu,R.C. de Lamare +1 more
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TLDR
Simulation results show that the VFAP-BP algorithm outperforms the standard BP algorithm, and requires a significantly smaller number of iterations when decoding either general or commercial LDPC codes.Abstract:
In this paper we propose a novel message passing algorithm which exploits the existence of short cycles to obtain performance gains by reweighting the factor graph. The proposed decoding algorithm is called variable factor appearance probability belief propagation (VFAP-BP) algorithm and is suitable for wireless communications applications with low-latency and short blocks. Simulation results show that the VFAP-BP algorithm outperforms the standard BP algorithm, and requires a significantly smaller number of iterations when decoding either general or commercial LDPC codes.read more
Citations
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Study of Coarse Quantization-Aware Block Diagonalization Algorithms for MIMO Systems with Low Resolution.
TL;DR: The sum-rates achieved by the proposed Coarse Quantization-Aware Block Diagonalization (CQA-BD) and its regularized version (C QA-RBD) are superior to those previously reported in the literature.
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Compressed Randomized UTV Decompositions for Low-Rank Approximations and Big Data Applications.
TL;DR: A novel rank-revealing matrix decomposition algorithm termed Compressed Randomized UTV (CoR-UTV) decomposition is introduced along with a CoR- UTV variant aided by the power method technique.
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Optimizing Reweighted Belief Propagation for Distributed Likelihood Fusion Problems
TL;DR: In this article, a linear formulation of belief propagation is proposed for distributed likelihood fusion problems, which are characterized by equality constraints along possibly short cycles and analytically derive convergence conditions for certain types of graphs and optimize the convergence speed.
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Flexible Widely-Linear Multi-Branch Decision Feedback Detection Algorithms for Massive MIMO Systems.
TL;DR: A widely-linear multi-branch decision feedback receiver is developed to mitigate both the multiuser interference and the I/Q imbalance effects and results show that the proposed techniques outperform existing algorithms.
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Adaptive Decision Feedback Detection with Parallel Interference Cancellation and Constellation Constraints for Multi-Antenna Systems
Peng Li,Rodrigo C. de Lamare +1 more
TL;DR: Simulations show that the proposed P-DFCC technique has a complexity comparable to the conventional parallel decision feedback detector while it obtains a performance close to the maximum likelihood detector at a low to medium SNR range.
References
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Low-Density Parity-Check Codes
TL;DR: A simple but nonoptimum decoding scheme operating directly from the channel a posteriori probabilities is described and the probability of error using this decoder on a binary symmetric channel is shown to decrease at least exponentially with a root of the block length.
Journal ArticleDOI
A recursive approach to low complexity codes
TL;DR: It is shown that choosing a transmission order for the digits that is appropriate for the graph and the subcodes can give the code excellent burst-error correction abilities.
Journal ArticleDOI
Near Shannon limit performance of low density parity check codes
TL;DR: The authors report the empirical performance of Gallager's low density parity check codes on Gaussian channels, showing that performance substantially better than that of standard convolutional and concatenated codes can be achieved.
Journal ArticleDOI
A new class of upper bounds on the log partition function
TL;DR: A new class of upper bounds on the log partition function of a Markov random field (MRF) is introduced, based on concepts from convex duality and information geometry, and the Legendre mapping between exponential and mean parameters is exploited.
Journal ArticleDOI
Selective avoidance of cycles in irregular LDPC code construction
TL;DR: A Viterbi-like algorithm is proposed that selectively avoids small cycle clusters that are isolated from the rest of the graph and yields codes with error floors that are orders of magnitude below those of random codes with very small degradation in capacity-approaching capability.
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