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Deterministic identification (DI) has emerged as a promising paradigm for large-scale and goal-oriented communication systems. Despite significant progress, a fundamental open problem has remained unresolved: a persistent gap between the…

Information Theory · Computer Science 2026-04-14 Pau Colomer , Christian Deppe , Holger Boche , Andreas Winter

We study message identification over a q-ary uniform permutation channel, where the transmitted vector is permuted by a permutation chosen uniformly at random. For discrete memoryless channels(DMCs), the number of identifiable messages…

Information Theory · Computer Science 2024-09-23 Abhishek Sarkar , Bikash Kumar Dey

As sensing and instrumentation play an increasingly important role in systems controlled over wired and wireless networks, the need to better understand delay-sensitive communication becomes a prime issue. Along these lines, this article…

Information Theory · Computer Science 2021-03-26 Anoosheh Heidarzadeh , Jean-Francois Chamberland , Parimal Parag , Richard D. Wesel

A lower bound on the maximum likelihood (ML) decoding error exponent of linear block code ensembles, on the erasure channel, is developed. The lower bound turns to be positive, over an ensemble specific interval of erasure probabilities,…

Information Theory · Computer Science 2019-01-23 Enrico Paolini , Gianluigi Liva

Identification is a communication paradigm that promises exponential advantages over transmission for applications that do not actually require all messages to be reliably transmitted. Notably, the identification capacity theorems prove…

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

Memoryless channels with deletion errors as defined by a stochastic channel matrix allowing for bit drop outs are considered in which transmitted bits are either independently deleted with probability $d$ or unchanged with probability…

Information Theory · Computer Science 2012-11-13 Mojtaba Rahmati , Tolga M. Duman

This paper shows that the probability that the error exponent of a given code randomly generated from a pairwise independent ensemble being smaller than a lower bound on the typical random-coding exponent tends to zero as the codeword…

Information Theory · Computer Science 2022-04-04 Giuseppe Cocco , Albert Guillén i Fàbregas , Josep Font-Segura

We investigate the achievable error probability in communication over an AWGN discrete time memoryless channel with noiseless delay-less rate-limited feedback. For the case where the feedback rate R_FB is lower than the data rate R…

Information Theory · Computer Science 2012-04-24 Reza Mirghaderi , Andrea Goldsmith , Tsachy Weissman

We consider the problem of performing linear regression over a stream of $d$-dimensional examples, and show that any algorithm that uses a subquadratic amount of memory exhibits a slower rate of convergence than can be achieved without…

Machine Learning · Computer Science 2020-10-13 Vatsal Sharan , Aaron Sidford , Gregory Valiant

We consider a new formulation of a class of synchronization error channels and derive analytical bounds and numerical estimates for the capacity of these channels. For the binary channel with only deletions, we obtain an expression for the…

Information Theory · Computer Science 2016-11-17 Aravind R. Iyengar , Paul H. Siegel , Jack K. Wolf

Many communication applications incorporate event-triggered behavior, where the conventional Shannon capacity may not effectively gauge performance. Consequently, we advocate for the concept of identification capacity as a more suitable…

Information Theory · Computer Science 2025-02-04 Ilya Vorobyev , Christian Deppe , Holger Boche

We consider the discrete memoryless asymmetric 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…

Information Theory · Computer Science 2020-08-11 Yasutada Oohama

We study the problem of generating an approximately i.i.d. string at the output of a discrete memoryless channel using a limited amount of randomness at its input in presence of causal noiseless feedback. Feedback does not decrease the…

Information Theory · Computer Science 2016-09-29 Mani Bastani Parizi , Emre Telatar

In the last few years the so--called "linear deterministic" model of relay channels has gained popularity as a means of studying the flow of information over wireless communication networks, and this approach generalizes the model of…

Information Theory · Computer Science 2009-04-17 S. M. Sadegh Tabatabaei Yazdi , Serap A. Savari

The listsize capacity of a discrete memoryless channel is the largest transmission rate for which the expectation---or, more generally, the $\rho$-th moment---of the number of messages that could have produced the output of the channel…

Information Theory · Computer Science 2014-10-16 Christoph Bunte , Amos Lapidoth

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

A unified framework to obtain all known lower bounds (random coding, typical random coding and expurgated bound) on the reliability function of a point-to-point discrete memoryless channel (DMC) is presented. By using a similar idea for a…

Information Theory · Computer Science 2010-10-08 Ali Nazari , Achilleas Anastasopoulos , S. Sandeep Pradhan

A minimax converse for the identification via channels is derived. By this converse, a general formula for the identification capacity, which coincides with the transmission capacity, is proved without the assumption of the strong converse…

Information Theory · Computer Science 2021-01-15 Shun Watanabe

Ridge leverage scores provide a balance between low-rank approximation and regularization, and are ubiquitous in randomized linear algebra and machine learning. Deterministic algorithms are also of interest in the moderately big data…

Statistics Theory · Mathematics 2018-12-27 Shannon R. McCurdy