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相关论文: Window Processing of Binary Polarization Kernels

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Linear Programming (LP) decoding is emerging as an attractive alternative to decode Low-Density Parity-Check (LDPC) codes. However, the earliest LP decoders proposed for binary and nonbinary LDPC codes are not suitable for use at moderate…

信息论 · 计算机科学 2011-02-17 Mayur Punekar , Mark F. Flanagan

A family of polarizing kernels is presented together with polynomial-complexity algorithm for computing scaling exponent. The proposed convolutional polar kernels are based on convolutional polar codes, also known as b-MERA codes. For these…

信息论 · 计算机科学 2020-08-27 Ruslan Morozov

The problem of communication over binary dirty paper (DP) using nested polar codes is considered. An improved scheme, focusing on low delay, short to moderate blocklength communication is proposed. Successive cancellation list (SCL)…

信息论 · 计算机科学 2019-04-05 Barak Beilin , David Burshtein

In this paper, we propose a reinforcement learning based algorithm for rate-profile construction of Arikan's Polarization Assisted Convolutional (PAC) codes. This method can be used for any blocklength, rate, list size under successive…

信息论 · 计算机科学 2024-10-28 Samir Kumar Mishra , Digvijay Katyal , Sarvesha Anegundi Ganapathi

A generalization of the polar coding scheme called mixed-kernels is introduced. This generalization exploits several homogeneous kernels over alphabets of different sizes. An asymptotic analysis of the proposed scheme shows that its…

信息论 · 计算机科学 2015-03-25 Noam Presman , Ofer Shapira , Simon Litsyn

In this paper we propose an enhanced soft cancellation (SCAN) decoder for polar codes based on decoding stages permutation. The proposed soft cancellation list (SCANL) decoder runs $L$ independent SCAN decoders, each one relying on a…

信息论 · 计算机科学 2020-01-31 Charles Pillet , Carlo Condo , Valerio Bioglio

This paper introduces algorithms for the successive-cancellation decoding and the successive-cancellation list decoding of binary polar source/channel codes. By using the symmetric parametrization of conditional probability, we reduce both…

信息论 · 计算机科学 2021-01-22 Jun Muramatsu

This is the second part of a series of papers on a revisit to the bidirectional Bahl-Cocke-Jelinek-Raviv (BCJR) soft-in-soft-out (SISO) maximum a posteriori probability (MAP) decoding algorithm. Part I revisited the BCJR MAP decoding…

信息论 · 计算机科学 2018-01-16 Qimin You , Yonghui Li , Soung Chang Liew , Branka Vucetic

Wyner's work on wiretap channels and the recent works on information theoretic security are based on random codes. Achieving information theoretical security with practical coding schemes is of definite interest. In this note, the attempt…

信息论 · 计算机科学 2010-03-09 O. Ozan Koyluoglu , Hesham El Gamal

In this work, we introduce a deep learning-based polar code construction algorithm. The core idea is to represent the information/frozen bit indices of a polar code as a binary vector which can be interpreted as trainable weights of a…

信息论 · 计算机科学 2019-09-30 Moustafa Ebada , Sebastian Cammerer , Ahmed Elkelesh , Stephan ten Brink

A method of channel polarization, proposed by Arikan, allows us to construct efficient capacity-achieving channel codes. In the original work, binary input discrete memoryless channels are considered. A special case of $q$-ary channel…

信息论 · 计算机科学 2010-07-22 Ryuhei Mori , Toshiyuki Tanaka

The training complexity of deep learning-based channel decoders scales exponentially with the codebook size and therefore with the number of information bits. Thus, neural network decoding (NND) is currently only feasible for very short…

信息论 · 计算机科学 2017-02-23 Sebastian Cammerer , Tobias Gruber , Jakob Hoydis , Stephan ten Brink

It is shown that for any binary-input discrete memoryless channel $W$ with symmetric capacity $I(W)$ and any rate $R <I(W)$, the probability of block decoding error for polar coding under successive cancellation decoding satisfies $P_e \le…

信息论 · 计算机科学 2009-04-06 Erdal Arikan , Emre Telatar

Polar codes have received growing attention in the past decade and have been selected as the coding scheme for the control channel in the fifth generation (5G) wireless communication systems. However, the conventional polar codes have only…

信息论 · 计算机科学 2023-01-26 Hossein Rezaei , Nandana Rajatheva , Matti Latva-aho

Research on polar codes has been constantly gaining attention over the last decade, by academia and industry alike, thanks to their capacity-achieving error-correction performance and low-complexity decoding algorithms. Recently, they have…

信息论 · 计算机科学 2020-06-25 Carlo Condo , Valerio Bioglio , Ingmar Land

Polar codes are the first proven capacity-achieving codes. Recently, they are adopted as the channel coding scheme for 5G due to their superior performance.A polar code for encoding length-K information bits in length-N codeword could be…

信息论 · 计算机科学 2018-05-09 Yue Zhou , Rong Li , Huazi Zhang , Hejia Luo , Jun Wang

A novel search method for large polarization kernels is proposed. The algorithm produces a kernel with given partial distances by employing the depth-first search combined with the computation of coset leaders weight tables and sufficient…

信息论 · 计算机科学 2023-10-13 Grigorii Trofimiuk

Channel polarization is a method of constructing capacity achieving codes for symmetric binary-input discrete memoryless channels (B-DMCs) [1]. In the original paper, the construction complexity is exponential in the blocklength. In this…

信息论 · 计算机科学 2009-05-23 Ryuhei Mori , Toshiyuki Tanaka

Transmission of information reliably and efficiently across channels is one of the fundamental goals of coding and information theory. In this respect, efficiently decodable deterministic coding schemes which achieve capacity provably have…

信息论 · 计算机科学 2015-10-20 Vishvajeet Nagargoje

The recently-discovered polar codes are widely seen as a major breakthrough in coding theory. These codes achieve the capacity of many important channels under successive cancellation decoding. Motivated by the rapid progress in the theory…

硬件体系结构 · 计算机科学 2015-03-17 Camille Leroux , Ido Tal , Alexander Vardy , Warren J. Gross