Results 171 to 180 of about 1,239,425 (219)

Pipelined belief propagation polar decoders

2016 IEEE International Symposium on Circuits and Systems (ISCAS), 2016
Due to its inherent higher parallelism over successive cancellation (SC) polar decoder, belief propagation (BP) polar decoder becomes more favorable for high throughput applications. However, most existing BP decoders suffer from low utilization. In this paper, a new updating scheme, in which both left-to-right and right-to-left messages are considered
Junmei Yang, Chuan Zhang 0001, Huayi Zhou 0002, Xiaohu You 0001   +3 more
openaire   +1 more source

Autogeneration of Pipelined Belief Propagation Polar Decoders

IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2020
Though belief propagation (BP) polar decoders can achieve higher throughput than successive-cancellation (SC)-based decoders, and how to efficiently generate different belief propagation decoders (BPDs) which can meet various design specifications remains challenging. To this end, an autogeneration, which can translate the generation formula of BPDs to
Chao Ji, Yifei Shen 0003, Zaichen Zhang, Xiaohu You 0001, Chuan Zhang 0001   +4 more
openaire   +1 more source

Decoding with belief propagation

2009
AbstractThis chapter revisits the problem of decoding low density parity check (LDPC) codes. The maximum a posteriori probability (MAP) decoding of a bit is described as a statistical inference problem, and belief propagation is applied to its solution.
Marc Mézard, Andrea Montanari
openaire   +1 more source

Shuffled belief propagation decoding

Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002., 2003
In this paper, we propose a shuffled version of the belief propagation (BP) algorithm for the decoding of low-density parity-check (LDPC) codes. We show that when the Tanner graph of the code is acyclic and connected, the proposed scheme is optimal in the sense of MAP decoding and converges faster (or at least no slower) than the standard BP algorithm.
null Juntan Zhang, M. Fossorier
openaire   +1 more source

Enhancing Belief Propagation Decoding of Polar Codes: A Reinforcement Learning Approach

IEEE Communications Letters
Short block-length polar-like codes showcase exceptional error correction performance (ECP) using sequential decoding or successive cancellation list decoding with a large list size.
Mohsen Moradi, Salman Habib, David G. M. Mitchell   +2 more
semanticscholar   +1 more source

An Enhanced Belief Propagation Decoding Algorithm With Bit-Flipping for Polar Codes

IEEE Communications Letters
For polar codes, bit-flipping strategy can significantly improve the error-correction performance of the belief propagation (BP) decoding. However, the existing BP flipping (BPF) decoding algorithms require many attempts, due to their inefficiency in ...
Zhong-Jun Yang, Li Chen
semanticscholar   +1 more source

Decimation Strategies for Belief Propagation Decoding of Quantum LDPC Codes

International Symposium on Turbo Codes and Iterative Information Processing
Due to code degeneracy and the graph structure of quantum low-density parity-check (QLDPC) codes, the performance of conventional belief propagation (BP) decoding can be poor.
Masoumeh Alinia, David G. M. Mitchell, Hanwen Yao, Henry D. Pfister   +3 more
semanticscholar   +1 more source

Design and Optimization of Tail-Biting Spatially Coupled Protograph LDPC Codes Under Shuffled Belief-Propagation Decoding

IEEE Communications Letters, 2020
In this letter, we conduct a comprehensive investigation on tail-biting (TB) spatially coupled protograph (SC-P) low-density parity-check (LDPC) codes under shuffled belief-propagation (BP) decoding.
Zhao-Jie Yang, Yi Fang, Guofa Cai, Guo-Hua Zhang, Ping-Ping Chen   +4 more
semanticscholar   +1 more source

Multi-Round Belief Propagation Decoding With Impulsive Perturbation for Short LDPC Codes

IEEE Wireless Communications Letters, 2020
The belief propagation (BP) decoding of short low-density parity check codes suffers from short cycles and trapping sets. A number of perturbation schemes have been proposed to overcome the limitation.
Hyunjae Lee, Yong-Sung Kil, Min Jang, Sang-Hyo Kim, Ok-Sun Park, Giyoon Park   +5 more
semanticscholar   +1 more source

Belief Propagation and Parallel Decoding

1999
Probabilistic reasoning can be modeled through the use of graphs — the vertices in the graphs represent random variables, while the edges represent dependencies between the random variables. Such representations play a fundamental role in the development of expert systems, in part because they allow for a rapid factorization and evaluation of the joint
Chris Heegard, Stephen B. Wicker
openaire   +1 more source