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We generalize the random coding argument of stabilizer codes and derive a lower bound on the quantum capacity of an arbitrary discrete memoryless quantum channel. For the depolarizing channel, our lower bound coincides with that obtained by…

Quantum Physics · Physics 2007-05-23 Ryutaroh Matsumoto , Tomohiko Uyematsu

This paper studies an almost-lossless source-channel coding scheme in which source messages are assigned to different classes and encoded with a channel code that depends on the class index. The code performance is analyzed by means of…

In this paper, we give a distributed joint source channel coding scheme for arbitrary correlated sources for arbitrary point in the Slepian-Wolf rate region, and arbitrary link capacities using LDPC codes. We consider the Slepian-Wolf…

Information Theory · Computer Science 2008-02-20 Vaneet Aggarwal

We investigate the computation of Csiszar's bounds for the joint source-channel coding (JSCC) error exponent, E_J, of a communication system consisting of a discrete memoryless source and a discrete memoryless channel. We provide equivalent…

Information Theory · Computer Science 2007-07-13 Y. Zhong , F. Alajaji , L. L. Campbell

The optimization of joint source and channel coding for a sequence of numerous progressive packets is a challenging problem. Further, the problem becomes more complicated if the space-time coding is also involved with the optimization in a…

Information Theory · Computer Science 2017-09-18 Meesue Shin , Laura Toni , Sang-Hyo Kim , Seok-Ho Chang

Computation of the undetected error probability for error correcting codes over the Z-channel is an important issue, explored only in part in previous literature. In this paper we consider the case of Varshamov-Tenengol'ts codes, by…

Information Theory · Computer Science 2009-10-20 Marco Baldi , Franco Chiaraluce , Torleiv Kløve

The Gilbert--Varshamov (GV) bound is a classical existential result in coding theory. It implies that a random linear binary code of rate $\epsilon^2$ has relative distance at least $\frac{1}{2} - O(\epsilon)$ with high probability.…

Information Theory · Computer Science 2024-07-11 Dean Doron , Jonathan Mosheiff , Mary Wootters

This paper investigates the general distributed lossless/lossy source coding formulated by Jana and Blahut. Their multi-letter rate-distortion region, an alternative to the region derived by Yang and Qin, is characterized by entropy…

Information Theory · Computer Science 2024-07-08 Jun Muramatsu

Capacity formulas and random-coding exponents are derived for a generalized family of Gel'fand-Pinsker coding problems. These exponents yield asymptotic upper bounds on the achievable log probability of error. In our model, information is…

Information Theory · Computer Science 2007-07-13 Pierre Moulin , Ying Wang

We present and analyze a joint source-channel coding strategy for the transmission of a Gaussian source across a Gaussian channel in n channel uses per source symbol. Among all such strategies, our scheme has the following properties: i)…

Information Theory · Computer Science 2016-11-18 Marius Kleiner , Bixio Rimoldi

We propose a joint source-channel-network coding scheme, based on compressive sensing principles, for wireless networks with AWGN channels (that may include multiple access and broadcast), with sources exhibiting temporal and spatial…

Information Theory · Computer Science 2011-10-04 Soheil Feizi , Muriel Medard

In this work we investigate the behavior of the distortion threshold that can be guaranteed in joint source-channel coding, to within a prescribed excess-distortion probability. We show that the gap between this threshold and the optimal…

Information Theory · Computer Science 2011-12-08 Da Wang , Amir Ingber , Yuval Kochman

We derive simplified sphere-packing and Gilbert--Varshamov bounds for codes in the sum-rank metric, which can be computed more efficiently than previous ones. They give rise to asymptotic bounds that cover the asymptotic setting that has…

Information Theory · Computer Science 2023-03-22 Cornelia Ott , Sven Puchinger , Martin Bossert

We consider the problem of distributed joint source-channel coding of correlated Gaussian sources over a Gaussian Multiple Access Channel (GMAC). There may be side information at the decoder and/or at the encoders. First we specialize a…

Information Theory · Computer Science 2009-05-15 R Rajesh , Vinod Sharma

Stochastic encoders for channel coding and lossy source coding are introduced with a rate close to the fundamental limits, where the only restriction is that the channel input alphabet and the reproduction alphabet of the lossy source code…

Information Theory · Computer Science 2016-11-15 Jun Muramatsu

A new approach to joint source-channel coding is presented in the context of communicating correlated sources over multiple access channels. Similar to the separation architecture, the joint source-channel coding system architecture in this…

Information Theory · Computer Science 2013-06-04 Paolo Minero , Sung Hoon Lim , Young-Han Kim

Conventional communication systems, including both separation-based coding and AI-driven joint source-channel coding (JSCC), are largely guided by Shannon's rate-distortion theory. However, relying on generic distortion metrics fails to…

Information Theory · Computer Science 2026-01-21 Tong Wu , Zhiyong Chen , Guo Lu , Li Song , Feng Yang , Meixia Tao , Wenjun Zhang

Cumulative weight enumerators of random linear codes are introduced, their asymptotic properties are studied, and very sharp thresholds are exhibited; as a consequence, it is shown that the asymptotic Gilbert-Varshamov bound is a very sharp…

Information Theory · Computer Science 2012-12-27 Yun Fan , San Ling , Hongwei Liu , Jing Shen , Chaoping Xing

We present new constructions of codes for asymmetric channels for both binary and nonbinary alphabets, based on methods of generalized code concatenation. For the binary asymmetric channel, our methods construct nonlinear…

Information Theory · Computer Science 2015-04-15 Markus Grassl , Peter Shor , Graeme Smith , John Smolin , Bei Zeng

We study the problem of retrieving data from a channel that breaks the input sequence into a set of unordered fragments of random lengths, which we refer to as the chop-and-shuffle channel. The length of each fragment follows a geometric…

Information Theory · Computer Science 2022-01-12 Sajjad Nassirpour , Ilan Shomorony , Alireza Vahid