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Shaping codes are used to encode information for use on channels with cost constraints. Applications include data transmission with a power constraint and, more recently, data storage on flash memories with a constraint on memory cell wear.…

Information Theory · Computer Science 2020-01-10 Yi Liu , Pengfei Huang , Alexander W. Bergman , Paul H. Siegel

Data shaping is a coding technique that has been proposed to increase the lifetime of flash memory devices. Several data shaping codes have been described in recent work, including endurance codes and direct shaping codes for structured…

Information Theory · Computer Science 2017-04-20 Yi Liu , Pengfei Huang , Paul H. Siegel

This paper finds new tight finite-blocklength bounds for the best achievable lossy joint source-channel code rate, and demonstrates that joint source-channel code design brings considerable performance advantage over a separate one in the…

Information Theory · Computer Science 2014-02-05 Victoria Kostina , Sergio Verdú

We study the following semi-deterministic setting of the joint source-channel coding problem: a deterministic source sequence (a.k.a. individual sequence) is transmitted via a memoryless channel, using delay-limited encoder and decoder,…

Information Theory · Computer Science 2021-09-29 Neri Merhav

In this work, we study a recently proposed direct shaping code for flash memory. This rate-1 code is designed to reduce the wear for SLC (one bit per cell) flash by minimizing the average fraction of programmed cells when storing structured…

Information Theory · Computer Science 2020-07-14 Yi Liu , Paul H. Siegel

A real time coding system with lookahead consists of a memoryless source, a memoryless channel, an encoder, which encodes the source symbols sequentially with knowledge of future source symbols upto a fixed finite lookahead, d, with or…

Information Theory · Computer Science 2011-05-31 Himanshu Asnani , Tsachy Weissman

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 scheme is proposed that combines probabilistic signal shaping with bit-metric decoding. The transmitter generates symbols according to a distribution on the channel input alphabet. The symbols are labeled by bit strings. At the receiver,…

Information Theory · Computer Science 2014-04-22 Georg Böcherer

In this study we consider rateless coding over discrete memoryless channels (DMC) with feedback. Unlike traditional fixed-rate codes, in rateless codes each codeword is infinitely long, and the decoding time depends on the confidence level…

Information Theory · Computer Science 2012-01-30 Navot Blits

We derive a general formula of the minimum achievable rate for fixed-to-variable length coding with a regular cost function by allowing the error probability up to a constant $\varepsilon$. For a fixed-to-variable length code, we call the…

Information Theory · Computer Science 2017-10-11 Hideki Yagi , Ryo Nomura

We study the problem of achieving strong secrecy over wiretap channels at negligible cost, in the sense of maintaining the overall communication rate of the same channel without secrecy constraints. Specifically, we propose and analyze two…

Information Theory · Computer Science 2016-12-06 Remi A. Chou , Badri Vellambi , Matthieu Bloch , Joerg Kliewer

This paper examines the maximum code rate achievable by a data-driven communication system over some unknown discrete memoryless channel in the finite blocklength regime. A class of channel codes, called learning-based channel codes, is…

Information Theory · Computer Science 2023-07-18 Neil Irwin Bernardo , Jingge Zhu , Jamie Evans

We consider coding schemes for computationally bounded channels, which can introduce an arbitrary set of errors as long as (a) the fraction of errors is bounded with high probability by a parameter $p$ and (b) the process which adds the…

Information Theory · Computer Science 2013-03-01 Venkatesan Guruswami , Adam Smith

We consider channel coding for discrete memoryless channels (DMCs) with a novel cost constraint that constrains both the mean and the variance of the cost of the codewords. We show that the maximum (asymptotically) achievable rate under the…

Information Theory · Computer Science 2025-01-23 Adeel Mahmood , Aaron B. Wagner

We study channel simulation under common randomness assistance in the finite-blocklength regime and identify the smooth channel max-information as a linear program one-shot converse on the minimal simulation cost for fixed error tolerance.…

Information Theory · Computer Science 2024-10-10 Michael X. Cao , Navneeth Ramakrishnan , Mario Berta , Marco Tomamichel

This paper investigates the first- and second-order maximum achievable rates of codes with/without cost constraints for mixed {channels} whose channel law is characterized by a general mixture of (at most) uncountably many stationary and…

Information Theory · Computer Science 2016-05-09 Hideki Yagi , Te Sun Han , Ryo Nomura

This paper considers the problem of channel coding with a given (possibly suboptimal) maximum-metric decoding rule. A cost-constrained random-coding ensemble with multiple auxiliary costs is introduced, and is shown to achieve error…

Information Theory · Computer Science 2014-03-05 Jonathan Scarlett , Alfonso Martinez , Albert Guillén i Fàbregas

In this paper, we investigate the optimal tradeoff between source and channel coding for channels with bit or packet erasure. Upper and Lower bounds on the optimal channel coding rate are computed to achieve minimal end-to-end distortion.…

Information Theory · Computer Science 2007-07-13 Sriram N. Kizhakkemadam , Panos Papamichalis , Mandyam Srinath , Dinesh Rajan

This paper proves the separation between source-network coding and channel coding in networks of noisy, discrete, memoryless channels. We show that the set of achievable distortion matrices in delivering a family of dependent sources across…

Information Theory · Computer Science 2016-11-17 Shirin Jalali , Michelle Effros

The arbitrarily varying channel (AVC) is a channel model whose state is selected maliciously by an adversary. Fixed-blocklength coding assumes a worst-case bound on the adversary's capabilities, which leads to pessimistic results. This…

Information Theory · Computer Science 2009-10-06 Anand D. Sarwate , Michael Gastpar
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