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We address the problem of simulating an arbitrary Markovian interactive protocol over binary symmetric channels with crossover probability $\varepsilon$. We are interested in the achievable rates of reliable simulation, i.e., in…

Information Theory · Computer Science 2017-11-01 Assaf Ben-Yishai , Ofer Shayevitz , Young-Han Kim

The interactive capacity of a noisy channel is the highest possible rate at which arbitrary interactive protocols can be simulated reliably over the channel. Determining the interactive capacity is notoriously difficult, and the best known…

Information Theory · Computer Science 2021-02-03 Assaf Ben-Yishai , Young-Han Kim , Rotem Oshman , Ofer Shayevitz

We provide the first capacity approaching coding schemes that robustly simulate any interactive protocol over an adversarial channel that corrupts any $\epsilon$ fraction of the transmitted symbols. Our coding schemes achieve a…

Data Structures and Algorithms · Computer Science 2014-11-04 Bernhard Haeupler

The essential interactive capacity of a discrete memoryless channel is defined in this paper as the maximal rate at which the transcript of any interactive protocol can be reliably simulated over the channel, using a deterministic coding…

Information Theory · Computer Science 2021-08-13 Assaf Ben-Yishai , Young-Han Kim , Or Ordentlich , Ofer Shayevitz

Let $W$ be a binary-input memoryless symmetric (BMS) channel with Shannon capacity $I(W)$ and fix any $\alpha > 0$. We construct, for any sufficiently small $\delta > 0$, binary linear codes of block length $O(1/\delta^{2+\alpha})$ and rate…

Information Theory · Computer Science 2022-01-25 Venkatesan Guruswami , Andrii Riazanov , Min Ye

Shannon defined channel capacity as the highest rate at which there exists a sequence of codes of block length $n$ such that the error probability goes to zero as $n$ goes to infinity. In this definition, it is implicit that the block…

Information Theory · Computer Science 2010-06-03 Rui A. Costa , Michael Langberg , João Barros

Shannon-Hartley theorem can accurately calculate the channel capacity when the signal observation time is infinite. However, the calculation of finite-time capacity, which remains unknown, is essential for guiding the design of practical…

Information Theory · Computer Science 2021-12-17 Jieao Zhu , Zijian Zhang , Zhongzhichao Wan , Linglong Dai

A new channel coding approach was proposed in [1] for random multiple access communication over the discrete-time memoryless channel. The coding approach allows users to choose their communication rates independently without sharing the…

Information Theory · Computer Science 2016-11-15 Zheng Wang , Jie Luo

We study and compare the Shannon capacity region and the stable throughput region for a random access system in which source nodes multicast their messages to multiple destination nodes. Under an erasure channel model which accounts for…

Information Theory · Computer Science 2007-09-20 Brooke Shrader , Anthony Ephremides

We study the communication rate of coding schemes for interactive communication that transform any two-party interactive protocol into a protocol that is robust to noise. Recently, Haeupler (FOCS '14) showed that if an $\epsilon > 0$…

Information Theory · Computer Science 2016-05-31 Bernhard Haeupler , Ameya Velingker

In this paper, we propose a multiple-input multipleoutput (MIMO) transmission strategy that is closer to the Shannon limit than the existing strategies. Different from most existing strategies which only consider uniformly distributed…

Information Theory · Computer Science 2021-07-01 Jie Feng , Biqian Feng , Yongpeng Wu , Li Shen , Wenjun Zhang

We give trade-offs between classical communication, quantum communication, and entanglement for processing information in the Shannon-theoretic setting. We first prove a unit-resource capacity theorem that applies to the scenario where only…

Quantum Physics · Physics 2010-08-23 Min-Hsiu Hsieh , Mark M. Wilde

We prove that, for all binary-input symmetric memoryless channels, polar codes enable reliable communication at rates within $\epsilon > 0$ of the Shannon capacity with a block length, construction complexity, and decoding complexity all…

Information Theory · Computer Science 2013-11-19 Venkatesan Guruswami , Patrick Xia

This paper presents an analysis of spinal codes, a class of rateless codes proposed recently. We prove that spinal codes achieve Shannon capacity for the binary symmetric channel (BSC) and the additive white Gaussian noise (AWGN) channel…

Information Theory · Computer Science 2012-06-05 Hari Balakrishnan , Peter Iannucci , Jonathan Perry , Devavrat Shah

A central question in information theory is to determine the maximum success probability that can be achieved in sending a fixed number of messages over a noisy channel. This was first studied in the pioneering work of Shannon who…

Information Theory · Computer Science 2018-06-25 Siddharth Barman , Omar Fawzi

In secure multi-party computations (SMC), parties wish to compute a function on their private data without revealing more information about their data than what the function reveals. In this paper, we investigate two Shannon-type questions…

Information Theory · Computer Science 2017-05-25 Eun Jee Lee , Emmanuel Abbe

Proving achievability of protocols in quantum Shannon theory usually does not consider the efficiency at which the goal of the protocol can be achieved. Nevertheless it is known that protocols such as coherent state merging are efficiently…

Quantum Physics · Physics 2015-03-17 Christoph Hirche , Ciara Morgan

Given a quantum Markovian noise model, we study the maximum dimension of a classical or quantum system that can be stored for arbitrarily large time. We show that, unlike the fixed time setting, in the limit of infinite time, the classical…

Quantum Physics · Physics 2025-02-27 Omar Fawzi , Mizanur Rahaman , Mostafa Taheri

We propose an iterative method for approximately computing the capacity of discrete memoryless channels, possibly under additional constraints on the input distribution. Based on duality of convex programming, we derive explicit upper and…

Information Theory · Computer Science 2015-04-06 Tobias Sutter , David Sutter , Peyman Mohajerin Esfahani , John Lygeros

Shannon's analysis of the fundamental capacity limits for memoryless communication channels has been refined over time. In this paper, the maximum volume $M_\avg^*(n,\epsilon)$ of length-$n$ codes subject to an average decoding error…

Information Theory · Computer Science 2016-12-28 Pierre Moulin
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