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The I-MMSE formula connects two important quantities in information theory and estimation theory: the mutual information and the minimum mean-squared error (MMSE). It states that in a scalar Gaussian channel, the derivative of the mutual…

Information Theory · Computer Science 2024-08-27 Minh-Toan Nguyen

We analyze the problem of estimating a signal from multiple measurements on a $\mbox{group action channel}$ that linearly transforms a signal by a random group action followed by a fixed projection and additive Gaussian noise. This channel…

Information Theory · Computer Science 2018-01-16 Emmanuel Abbe , João M. Pereira , Amit Singer

This paper considers the problem of transmitting the difference of two jointly Gaussian sources over a two-user additive Gaussian noise multiple access channel (MAC). The goal is to recover this difference within an average mean squared…

Information Theory · Computer Science 2008-12-08 Rajiv Soundararajan , Sriram Vishwanath

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

We address the problem of signal denoising via transform-domain shrinkage based on a novel $\textit{risk}$ criterion called the minimum probability of error (MPE), which measures the probability that the estimated parameter lies outside an…

Applications · Statistics 2020-02-19 Jishnu Sadasivan , Subhadip Mukherjee , Chandra Sekhar Seelamantula

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

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

The reconciliation step of continuous-variable quantum key distribution protocols usually involves forward error correction codes. Matching the code rate and the signal-to-noise ratio (SNR) of the quantum channel is required to achieve the…

Quantum Physics · Physics 2019-05-14 Sören Kreinberg , Igor Koltchanov , André Richter

We present new fundamental results for the mean square error (MSE)-optimal conditional mean estimator (CME) in one-bit quantized systems for a Gaussian mixture model (GMM) distributed signal of interest, possibly corrupted by additive white…

Signal Processing · Electrical Eng. & Systems 2024-07-02 Benedikt Fesl , Wolfgang Utschick

A bound on the maximum information transmission rate through a cascade of Gaussian links is presented. The network model consists of a source node attempting to send a message drawn from a finite alphabet to a sink, through a cascade of…

Information Theory · Computer Science 2013-01-29 Ramanan Subramanian , Badri Vellambi , Ingmar Land

In this paper, we generalize the fundamental relation between the mutual information and the minimum mean squared error (MMSE) by Guo, Shamai, and Verdu [1] to K-User Gaussian channels. We prove that the derivative of the multiuser mutual…

Information Theory · Computer Science 2017-04-20 Samah A. M. Ghanem

We consider large-scale linear inverse problems in Bayesian settings. We follow a recent line of work that applies the approximate message passing (AMP) framework to multi-processor (MP) computational systems, where each processor node…

Information Theory · Computer Science 2016-11-09 Junan Zhu , Dror Baron , Ahmad Beirami

This paper considers the problem of symbol detection in massive multiple-input multiple-output (MIMO) wireless communication systems. We consider hard-thresholding preceeded by two variants of the regularized least squares (RLS) decoder;…

Information Theory · Computer Science 2023-08-11 Ayed M. Alrashdi , Abla Kammoun , Ali H. Muqaibel , Tareq Y. Al-Naffouri

Minimum mean square error (MMSE) estimation of block sparse signals from noisy linear measurements is considered. Unlike in the standard compressive sensing setup where the non-zero entries of the signal are independently and uniformly…

Information Theory · Computer Science 2012-04-26 Mikko Vehkaperä , Saikat Chatterjee , Mikael Skoglund

Since its development, the minimax framework has been one of the corner stones of theoretical statistics, and has contributed to the popularity of many well-known estimators, such as the regularized M-estimators for high-dimensional…

Statistics Theory · Mathematics 2024-01-01 Yilin Guo , Haolei Weng , Arian Maleki

We consider the task of estimating a low-rank matrix from non-linear and noisy observations. We prove a strong universality result showing that Bayes-optimal performances are characterized by an equivalent Gaussian model with an effective…

Machine Learning · Statistics 2024-03-08 Pierre Mergny , Justin Ko , Florent Krzakala , Lenka Zdeborová

Denoising has to do with estimating a signal $x_0$ from its noisy observations $y=x_0+z$. In this paper, we focus on the "structured denoising problem", where the signal $x_0$ possesses a certain structure and $z$ has independent normally…

Information Theory · Computer Science 2013-11-15 Samet Oymak , Babak Hassibi

A multiple access channel and a point-to-point channel sharing the same medium for communications are considered. We obtain an outer bound for the capacity region of this setup, and we show that this outer bound is achievable in some cases.…

Information Theory · Computer Science 2010-11-01 Anas Chaaban , Aydin Sezgin

We study large deviation upper bounds and mean-squared error (MSE) guarantees of a general framework of nonlinear stochastic gradient methods in the online setting, in the presence of heavy-tailed noise. Unlike existing works that rely on…

Machine Learning · Computer Science 2025-03-25 Aleksandar Armacki , Shuhua Yu , Dragana Bajovic , Dusan Jakovetic , Soummya Kar

For the discrete-time additive white generalized Gaussian noise channel with a generalized input power constraint, with the respective shape and power parameters >= 1, we derive an upper bound on the optimal block error exponent. Explicit…

Information Theory · Computer Science 2025-09-11 Sergey Tridenski , Anelia Somekh-Baruch
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