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We focus on designing error-correcting codes for the symmetric Gaussian broadcast channel with feedback. Feedback not only expands the capacity region of the broadcast channel but also enhances transmission reliability. In this work, we…

Information Theory · Computer Science 2025-03-04 Yingyao Zhou , Natasha Devroye

This paper studies the coherent and non-coherent multiuser multiple-input multiple-output (MU-MIMO) uplink system in the finite blocklength regime. The i.i.d. Gaussian codebook is assumed for each user. To be more specific, the BS first…

Information Theory · Computer Science 2022-10-04 Junjuan Feng , Hien Quoc Ngo , Michail Matthaiou

This paper explores the computational complexity involved in determining the capacity of the band-limited additive colored Gaussian noise (ACGN) channel and its capacity-achieving power spectral density (p.s.d.). The study reveals that when…

Information Theory · Computer Science 2023-10-11 Holger Boche , Andrea Grigorescu , Rafael F. Schaefer , H. Vincent Poor

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

A new achievable rate for bit-metric decoding (BMD) is derived using random coding arguments. The rate expression can be evaluated for any input distribution, and in particular the bit-levels of binary input labels can be stochastically…

Information Theory · Computer Science 2016-05-31 Georg Böcherer

We study the maximum achievable differential entropy at the output of a system assigning to each input X the sum X+N, with N a given noise with probability law absolutely continuous with respect to the Lebesgue measure and where the input…

Optimization and Control · Mathematics 2016-02-04 Francisco J. Piera

This paper considers the problem of variable-length coding over a discrete memoryless channel (DMC) with noiseless feedback. The paper provides a stochastic control view of the problem whose solution is analyzed via a newly proposed…

Information Theory · Computer Science 2016-11-18 Mohammad Naghshvar , Tara Javidi , Michèle Wigger

This paper quantifies the intuitive observation that adding noise reduces available information by means of non-linear strong data processing inequalities. Consider the random variables $W\to X\to Y$ forming a Markov chain, where $Y=X+Z$…

Information Theory · Computer Science 2017-11-21 Flavio P. Calmon , Yury Polyanskiy , Yihong Wu

This paper considers the achievable rates and decoding complexity of low-density parity-check (LDPC) codes over statistically independent parallel channels. The paper starts with the derivation of bounds on the conditional entropy of the…

Information Theory · Computer Science 2007-07-13 Igal Sason , Gil Wiechman

We derive upper and lower bounds on the reliability function for the common-message discrete memoryless broadcast channel with variable-length feedback. We show that the bounds are tight when the broadcast channel is stochastically…

Information Theory · Computer Science 2017-01-13 Lan V. Truong , Vincent Y. F. Tan

This work considers a Poisson noise channel with an amplitude constraint. It is well-known that the capacity-achieving input distribution for this channel is discrete with finitely many points. We sharpen this result by introducing upper…

Information Theory · Computer Science 2021-07-30 Alex Dytso , Luca Barletta , Shlomo Shamai

The paper introduces new bounds on the asymptotic density of parity-check matrices and the achievable rates under ML decoding of binary linear block codes transmitted over memoryless binary-input output-symmetric channels. The lower bounds…

Information Theory · Computer Science 2007-07-13 Gil Wiechman , Igal Sason

A tight converse bound to channel coding rate in the finite block-length regime and under AWGN conditions was recently proposed by Polyanskiy, Poor, and Verdu (PPV). The bound is a generalization of a number of other classical results, and…

Information Theory · Computer Science 2016-06-16 Tomaso Erseghe

Achievable error exponents for the one-way with noisy feedback and two-way AWGN channels are derived for the transmission of a finite number of messages $M$ using fixed block length $n$, under the almost sure (AS) and the expected block…

Information Theory · Computer Science 2019-01-23 Kenneth Palacio-Baus , Natasha Devroye

We derive lower and upper bounds on the identification capacity of inverse Gaussian channels, a fundamental model for molecular communications in fluid environments. The analysis considers deterministic encoding schemes under a peak time…

Information Theory · Computer Science 2026-05-08 Mohammad Javad Salariseddigh

Recent outer bounds on the capacity region of Gaussian interference channels are generalized to $m$-user channels with $m>2$ and asymmetric powers and crosstalk coefficients. The bounds are again shown to give the sum-rate capacity for…

Information Theory · Computer Science 2008-01-16 Xiaohu Shang , Gerhard Kramer , Biao Chen

An additive noise channel is considered, in which the distribution of the noise is nonparametric and unknown. The problem of learning encoders and decoders based on noise samples is considered. For uncoded communication systems, the problem…

Information Theory · Computer Science 2021-11-17 Nir Weinberger

We prove new strong converse results in a variety of group testing settings, generalizing a result of Baldassini, Johnson and Aldridge. These results are proved by two distinct approaches, corresponding to the non-adaptive and adaptive…

Information Theory · Computer Science 2017-08-22 Oliver Johnson

Classical information theory typically assumes reliable receiver-side processing. We study remote inference when communication is noisy and the receiver itself is built from unreliable components under a finite redundancy budget. Under a…

Information Theory · Computer Science 2026-04-22 Zhenyu Liu , Yi Ma , Rahim Tafazolli

We consider Additive White Gaussian Noise channels and Discrete Memoryless channels when the transmitter harvests energy from the environment. These can model wireless sensor networks as well as Internet of Things. By providing a unifying…

Information Theory · Computer Science 2019-03-21 K Gautam Shenoy , Vinod Sharma
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