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Convolutional precoding in polarization-adjusted convolutional (PAC) codes can reduce the number of minimum weight codewords (a.k.a error coefficient) of polar codes. This can result in improving the error correction performance of (near)…

Information Theory · Computer Science 2022-12-02 Xinyi Gu , Mohammad Rowshan , Jinhong Yuan

This paper is focused on the performance analysis of binary linear block codes (or ensembles) whose transmission takes place over independent and memoryless parallel channels. New upper bounds on the maximum-likelihood (ML) decoding error…

Information Theory · Computer Science 2007-07-13 Igal Sason , Idan Goldenberg

We consider the discrete memoryless degraded broadcast channels. We prove that the error probability of decoding tends to one exponentially for rates outside the capacity region and derive an explicit lower bound of this exponent function.…

Information Theory · Computer Science 2015-04-23 Yasutada Oohama

Low Earth orbit (LEO) satellite systems experience significant Doppler effects due to high mobility. While Doppler shifts can be largely compensated, residual frequency uncertainty induces a structured form of channel uncertainty that can…

Information Theory · Computer Science 2026-02-05 Pablo Orellana , Zheng Li , Jean-Marc Kelif , Sheng Yang , Shlomo Shamai

We survey coding techniques that enable reliable transmission at rates that approach the capacity of an arbitrary discrete memoryless channel. In particular, we take the point of view of modern coding theory and discuss how recent advances…

Information Theory · Computer Science 2018-01-04 Marco Mondelli , S. Hamed Hassani , Rüdiger Urbanke

We consider the problem of estimating an upper bound on the capacity of a memoryless channel with unknown channel law and continuous output alphabet. A novel data-driven algorithm is proposed that exploits the dual representation of…

Information Theory · Computer Science 2024-01-25 Christian Häger , Erik Agrell

The two-receiver broadcast packet erasure channel with feedback and memory is studied. Memory is modeled using a finite-state Markov chain representing a channel state. Outer and inner bounds on the capacity region are derived when the…

Information Theory · Computer Science 2014-11-11 Michael Heindlmaier , Navid Reyhanian , Shirin Saeedi Bidokhti

We investigate the classical communication over quantum channels when assisted by no-signaling (NS) and positive-partial-transpose-preserving (PPT) codes, for which both the optimal success probability of a given transmission rate and the…

Quantum Physics · Physics 2018-07-16 Xin Wang , Wei Xie , Runyao Duan

Polar codes are a family of capacity-achieving codes that have explicit and low-complexity construction, encoding, and decoding algorithms. Decoding of polar codes is based on the successive-cancellation decoder, which decodes in a bit-…

Information Theory · Computer Science 2018-03-06 Boaz Shuval , Ido Tal

We consider the problem of modulation and estimation of a random parameter $U$ to be conveyed across a discrete memoryless channel. Upper and lower bounds are derived for the best achievable exponential decay rate of a general moment of the…

Information Theory · Computer Science 2016-11-17 Neri Merhav

We derive a single-letter upper bound to the mismatched-decoding capacity for discrete memoryless channels. The bound is expressed as the mutual information of a transformation of the channel, such that a maximum-likelihood decoding error…

Information Theory · Computer Science 2021-02-16 Ehsan Asadi Kangarshahi , Albert Guillén i Fàbregas

Inspired by the boolean discrepancy problem, we study the following optimization problem which we term \textsc{Spherical Discrepancy}: given $m$ unit vectors $v_1, \dots, v_m$, find another unit vector $x$ that minimizes $\max_i \langle x,…

Computational Complexity · Computer Science 2019-11-19 Chris Jones , Matt McPartlon

A concatenated coding scheme over binary memoryless symmetric (BMS) channels using a polarization transformation followed by outer sub-codes is analyzed. Achievable error exponents and upper bounds on the error rate are derived. The first…

Information Theory · Computer Science 2017-10-24 Dina Goldin , David Burshtein

Constrained machine learning enables fairness-aware training, physics-informed neural networks, and integration of symbolic domain knowledge into statistical models. Despite its practical importance, no general method exists for the…

Machine Learning · Computer Science 2026-05-20 Adam Bosák , Andrii Kliachkin , Jana Lepšová , Gilles Bareilles , Jakub Mareček

This paper studies the random-coding exponent of joint source-channel coding for a scheme where source messages are assigned to disjoint subsets (referred to as classes), and codewords are independently generated according to a distribution…

Information Theory · Computer Science 2014-02-19 Adrià Tauste Campo , Gonzalo Vazquez-Vilar , Albert Guillén i Fàbregas , Tobias Koch , Alfonso Martinez

We derive a new upper bound on the reliability function for channel coding over discrete memoryless channels. Our bounding technique relies on two main elements: (i) adding an auxiliary genie-receiver that reveals to the original receiver a…

Information Theory · Computer Science 2022-09-05 Anelia Somekh-Baruch

The highest information rate at which quantum error-correction schemes work reliably on a channel, which is called the quantum capacity, is proven to be lower bounded by the limit of the quantity termed coherent information maximized over…

Quantum Physics · Physics 2007-05-23 Mitsuru Hamada

We propose a three-module extension of score-based VAMP (SC-VAMP) for signal recovery in nonlinear channels, where the received signal is obtained by applying a nonlinearity to a linear mixture of the transmitted signal, followed by…

Information Theory · Computer Science 2026-04-22 Tadashi Wadayama , Takumi Takahashi

Integer least-squares problems, concerned with solving a system of equations where the components of the unknown vector are integer-valued, arise in a wide range of applications. In many scenarios the unknown vector is sparse, i.e., a large…

Information Theory · Computer Science 2015-06-18 Somsubhra Barik , Haris Vikalo

Proving super-polynomial size lower bounds for syntactic multilinear Algebraic Branching Programs(smABPs) computing an explicit polynomial is a challenging problem in Algebraic Complexity Theory. The order in which variables in…

Computational Complexity · Computer Science 2019-01-15 C. Ramya , B. V. Raghavendra Rao