English
Related papers

Related papers: Does Gaussian Approximation Work Well for The Long…

200 papers

This paper presents a definition of a construction for long polar codes. Recently, we know that partial order is a universal property of the construction with a sublinear complexity for polar codes. In order to describe the partial order,…

Information Theory · Computer Science 2017-08-15 Sinan Kahraman

We consider two problems related to polar codes. First is the problem of polar codes construction and analysis of their performance without Monte-Carlo method. The formulas proposed are the same as those in [Mori-Tanaka], yet we believe…

Information Theory · Computer Science 2012-07-19 Gregory Bonik , Sergei Goreinov , Nickolai Zamarashkin

In this paper, we study polar codes from a practical point of view. In particular, we study concatenated polar codes and rate-compatible polar codes. First, we propose a concatenation scheme including polar codes and Low-Density…

Information Theory · Computer Science 2011-07-28 Ali Eslami , Hossein Pishro-Nik

After the pursuit of seventy years, the invention of polar codes indicates that we have found the first capacity-achieving coding with low complexity construction and decoding, which is the great breakthrough of the coding theory in the…

Information Theory · Computer Science 2023-03-28 Kai Niu , Ping Zhang , Jincheng Dai , Zhongwei Si , Chao Dong

Polarization-adjusted convolutional (PAC) codes were recently proposed and arouse the interest of the channel coding community because they were shown to approach theoretical bounds for the (128,64) code size. In this letter, we propose…

Information Theory · Computer Science 2020-11-09 Thibaud Tonnellier , Warren J. Gross

Polar codes were recently introduced by Ar\i kan. They achieve the capacity of arbitrary symmetric binary-input discrete memoryless channels under a low complexity successive cancellation decoding strategy. The original polar code…

Information Theory · Computer Science 2009-01-26 Satish Babu Korada , Eren Sasoglu , Rudiger Urbanke

Obtaining a reduced description with particle and momentum flux densities outgoing from the microscopic equations of motion of the particles requires approximations. The usual method, we refer to as truncation method, is to zero Fourier…

Statistical Mechanics · Physics 2017-01-04 Hamid Seyed-Allaei , Lutz Schimansky-Geier , Mohammad Reza Ejtehadi

The min-sum approximation is widely used in the decoding of polar codes. Although it is a numerical approximation, hardly any penalties are incurred in practice. We give a theoretical justification for this. We consider the common case of a…

Information Theory · Computer Science 2025-03-04 Nir Chisnevski , Ido Tal , Shlomo Shamai

In this paper, we investigate a coupled polar code architecture that supports both local and global decoding. This local-global construction is motivated by practical applications in data storage and transmission where reduced-latency…

Information Theory · Computer Science 2023-01-09 Ziyuan Zhu , Wei Wu , Paul H. Siegel

Gaussian processes (GPs) are flexible, probabilistic, nonparametric models widely used in fields such as spatial statistics and machine learning. A drawback of Gaussian processes is their computational cost, with $O(N^3)$ time and $O(N^2)$…

Computation · Statistics 2026-05-20 Filippo Rambelli , Fabio Sigrist

This paper investigates properties of polar codes that can be potentially useful in real-world applications. We start with analyzing the performance of finite-length polar codes over the binary erasure channel (BEC), while assuming belief…

Information Theory · Computer Science 2012-11-12 Ali Eslami , H. Pishro-Nik

A wiretap channel is served as the fundamental model of physical layer security techniques, where the secrecy capacity of the Gaussian wiretap channel is proven to be achieved by Gaussian input. However, there remains a gap between the…

Information Theory · Computer Science 2024-11-12 Li Shen , Yongpeng Wu , Peihong Yuan , Chengshan Xiao , Xiang-Gen Xia , Wenjun Zhang

Quantum reading provides a general framework where to formulate the statistical discrimination of quantum channels. Several paths have been taken for such a problem. However, there is much to be done in the avenue of optimizing channel…

Information Theory · Computer Science 2022-06-22 Francisco Revson F. Pereira , Stefano Mancini

A Gaussian Process (GP) is a prominent mathematical framework for stochastic function approximation in science and engineering applications. This success is largely attributed to the GP's analytical tractability, robustness, non-parametric…

Machine Learning · Statistics 2022-05-19 Marcus M. Noack , Harinarayan Krishnan , Mark D. Risser , Kristofer G. Reyes

We present a method of constructing rate-compatible polar codes that are capacity-achieving with low-complexity sequential decoders. The proposed code construction allows for incremental retransmissions at different rates in order to adapt…

Information Theory · Computer Science 2016-01-29 Song-Nam Hong , Dennis Hui , Ivana Marić

Tuning a complex simulation code refers to the process of improving the agreement of a code calculation with respect to a set of experimental data by adjusting parameters implemented in the code. This process belongs to the class of inverse…

Computation · Statistics 2024-08-19 Yun Am Seo , Youngsaeng Lee , Jeong-Soo Park

A polar-coded modulation scheme for deep-space optical communication is proposed. The photon counting Poisson channel with pulse position modulation (PPM) is considered. We use the fact that PPM is particularly well suited to be used with…

Information Theory · Computer Science 2018-12-10 Delcho Donev , Georg Böcherer

Tailoring polar code construction for decoding algorithms beyond successive cancellation has remained a topic of significant interest in the field. However, despite the inherent nested structure of polar codes, the use of sequence models in…

Information Theory · Computer Science 2024-01-31 Sravan Kumar Ankireddy , S Ashwin Hebbar , Heping Wan , Joonyoung Cho , Charlie Zhang

Gaussian process (GP) regression is a flexible, nonparametric approach to regression that naturally quantifies uncertainty. In many applications, the number of responses and covariates are both large, and a goal is to select covariates that…

Methodology · Statistics 2022-10-12 Jian Cao , Joseph Guinness , Marc G. Genton , Matthias Katzfuss

We consider the problem of efficiently constructing polar codes over binary memoryless symmetric (BMS) channels. The complexity of designing polar codes via an exact evaluation of the polarized channels to find which ones are "good" appears…

Information Theory · Computer Science 2012-09-21 Ramtin Pedarsani , S. Hamed Hassani , Ido Tal , Emre Telatar