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The variable-length source coding problem allowing the error probability up to some constant is considered for general sources. In this problem the optimum mean codeword length of variable-length codes has already been determined. On the…

Information Theory · Computer Science 2018-10-19 Ryo Nomura , Hideki Yagi

We consider communication over the binary erasure channel (BEC) using low-density parity-check (LDPC) code and belief propagation (BP) decoding. The bit error probability for infinite block length is known by density evolution and it is…

Information Theory · Computer Science 2008-01-23 Ryuhei Mori , Kenta Kasai , Tomoharu Shibuya , Kohichi Sakaniwa

This paper considers the achievability and converse bounds on the maximal channel coding rate at a given blocklength and error probability over AWGN channels. The problem stems from covert communication with Gaussian codewords. By…

Information Theory · Computer Science 2021-01-01 Xinchun Yu , Shuangqin Wei , Yuan Luo

The fundamental limits of channels with mismatched decoding are addressed. A general formula is established for the mismatch capacity of a general channel, defined as a sequence of conditional distributions with a general decoding metrics…

Information Theory · Computer Science 2013-10-01 Anelia Somekh-Baruch

The analysis of random coding error exponents pertaining to erasure/list decoding, due to Forney, is revisited. Instead of using Jensen's inequality as well as some other inequalities in the derivation, we demonstrate that an exponentially…

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

The zero-error capacity of a classical channel is a parameter of its confusability graph, and is equal to the minimum of the values of graph parameters that are additive under the disjoint union, multiplicative under the strong product,…

Information Theory · Computer Science 2022-07-22 Péter Vrana

In contrast to a maximum-likelihood decoder, it is often desirable to use an incomplete decoder that can detect its decoding errors with high probability. One common choice is the bounded distance decoder. Bounds are derived for the total…

Information Theory · Computer Science 2012-07-26 Kenneth Andrews , Sam Dolinar

Traditional studies of multi-source, multi-terminal interference channels typically allow a vanishing probability of error in communication. Motivated by the study of network coding, this work addresses the task of quantifying the loss in…

Information Theory · Computer Science 2013-07-30 Ilia Levi , Dan Vilenchik , Michael Langberg , Michelle Effros

We introduce an expurgation method for source coding with side information that enables direct dual-domain derivations of expurgated error exponents. Dual-domain methods yield optimization problems over few parameters, with any sub-optimal…

Information Theory · Computer Science 2026-02-25 Mehdi Dabirnia , Hamdi Joudeh , Albert Guillén i Fàbregas

Guruswami and Indyk showed in [1] that Forney's error exponent can be achieved with linear coding complexity over binary symmetric channels. This paper extends this conclusion to general discrete-time memoryless channels and shows that…

Information Theory · Computer Science 2016-11-17 Zheng Wang , Jie Luo

This paper presents prefix codes which minimize various criteria constructed as a convex combination of maximum codeword length and average codeword length or maximum redundancy and average redundancy, including a convex combination of the…

Information Theory · Computer Science 2011-02-11 Charalambos D. Charalambous , Themistoklis Charalambous , Farzad Rezaei

A coding theorem and converse are proved for a large class of abstract stationary channels with time structure including the result by Kadota and Wyner (1972) on continuous-time real-valued channels as special cases. As main contribution…

Information Theory · Computer Science 2018-04-18 Martin Mittelbach , Eduard A. Jorswieck

An erasure channel with a fixed alphabet size $q$, where $q \gg 1$, is studied. It is proved that over any erasure channel (with or without memory), Maximum Distance Separable (MDS) codes achieve the minimum probability of error (assuming…

Information Theory · Computer Science 2008-06-06 Shervan Fashandi , Shahab Oveis Gharan , Amir K. Khandani

A new straightforward universal blind detection algorithm for linear Gaussian channel with ISI is given. A new error exponent is derived, which is better than Gallager's random coding error exponent.

Information Theory · Computer Science 2008-01-04 Lóránt Farkas

Erasure list decoding was introduced to correct a larger number of erasures with output of a list of possible candidates. In the present paper, we consider both random linear codes and algebraic geometry codes for list decoding erasure…

Information Theory · Computer Science 2014-01-14 Yang Ding , Lingfei Jin , Chaoping Xing

This paper concerns itself with the question of list decoding for general adversarial channels, e.g., bit-flip ($\textsf{XOR}$) channels, erasure channels, $\textsf{AND}$ ($Z$-) channels, $\textsf{OR}$ channels, real adder channels, noisy…

Information Theory · Computer Science 2019-09-11 Yihan Zhang , Amitalok J. Budkuley , Sidharth Jaggi

The reliability function of memoryless channels with noiseless feedback and variable-length coding has been found to be a linear function of the average rate in the classic work of Burnashev. In this work we consider unifilar channels with…

Information Theory · Computer Science 2017-07-11 Achilleas Anastasopoulos , Jui Wu

The problem of error control in random linear network coding is addressed from a matrix perspective that is closely related to the subspace perspective of K\"otter and Kschischang. A large class of constant-dimension subspace codes is…

Information Theory · Computer Science 2019-05-07 Danilo Silva , Frank R. Kschischang , Ralf Kötter

In this paper, we derive analytic expressions for the success probability of decoding (Partial) Unit Memory codes in memoryless channels. An applications of this result is that these codes outperform individual block codes in certain…

Information Theory · Computer Science 2017-05-25 Sven Puchinger , Sven Müelich , Martin Bossert

Over any discrete memoryless channel, we build codes such that: for one, their block error probabilities and code rates scale like random codes'; and for two, their encoding and decoding complexities scale like polar codes'. Quantitatively,…

Information Theory · Computer Science 2020-12-14 Hsin-Po Wang , Iwan Duursma
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