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Cellular systems are becoming more heterogeneous with the introduction of low power nodes including femtocells, relays, and distributed antennas. Unfortunately, the resulting interference environment is also becoming more complicated,…

Information Theory · Computer Science 2013-04-29 Robert W. Heath , Marios Kountouris , Tianyang Bai

We consider the elliptic Ginibre ensembles in the real, complex and symplectic symmetry classes. As the matrix size tends to infinity, we derive the asymptotic behaviour of the upper tail large deviation probabilities for both the spectral…

Probability · Mathematics 2026-03-18 Sung-Soo Byun , Yong-Woo Lee , Seungjoon Oh

We study the flow-level performance of random wireless networks. The locations of base stations (BSs) follow a Poisson point process. The number and positions of active users are dynamic. We associate a queue to each BS. The performance and…

Information Theory · Computer Science 2013-08-23 Richard Combes , Eitan Altman

Turing instability in activator-inhibitor systems provides a paradigm of nonequilibrium pattern formation; it has been extensively investigated for biological and chemical processes. Turing pattern formation should furthermore be possible…

Adaptation and Self-Organizing Systems · Physics 2010-05-13 Hiroya Nakao , Alexander S. Mikhailov

The nearest-neighbor level-spacing distributions are a fundamental quantity of disordered systems and universal. It is well-known that extended and localized states of random Hermitian systems follow the Wigner-Dyson and the Poison…

Disordered Systems and Neural Networks · Physics 2022-08-23 C. Wang , X. R. Wang

In wireless networks with random node distribution, the underlying point process model and the channel fading process are usually considered separately. A unified framework is introduced that permits the geometric characterization of fading…

Information Theory · Computer Science 2007-11-14 Martin Haenggi

In substations, the presence of random transient impulsive interference sources makes noise highly non-Gaussian. In this paper, the primary interest is to provide a general model for wireless channel in presence of these transient impulsive…

Methodology · Statistics 2015-04-28 Minh Au , Basile L. Agba , François Gagnon

We consider the eigenvalues of a large dimensional real or complex Ginibre matrix in the region of the complex plane where their real parts reach their maximum value. This maximum follows the Gumbel distribution and that these extreme…

Probability · Mathematics 2022-10-26 Giorgio Cipolloni , László Erdős , Dominik Schröder , Yuanyuan Xu

A family of random matrix ensembles interpolating between the GUE and the Ginibre ensemble of $n\times n$ matrices with iid centered complex Gaussian entries is considered. The asymptotic spectral distribution in these models is uniform in…

Probability · Mathematics 2010-03-23 Martin Bender

Master thesis at TU Berlin with Wolfgang K\"{o}nig, April 2016. We investigate a wireless network where the users are located according to a Poisson point process in a bounded subset of R^d, in the high-density limit. Assuming that the…

Probability · Mathematics 2016-06-22 András József Tóbiás

We study pattern formation in class of a large-dimensional neural networks posed on random graphs and subject to spatio-temporal stochastic forcing. Under generic conditions on coupling and nodal dynamics, we prove that the network admits a…

Probability · Mathematics 2025-08-26 Daniele Avitabile , James MacLaurin

An almost ubiquitous assumption made in the stochastic-analytic study of the quality of service in cellular networks is Poisson distribution of base stations. It is usually justified by various irregularities in the real placement of base…

Probability · Mathematics 2013-01-21 Bartlomiej Blaszczyszyn , Mohamed Kadhem Karray , Holger Paul Keeler

It has recently been observed that the SIR distributions of a variety of cellular network models and transmission techniques look very similar in shape. As a result, they are well approximated by a simple horizontal shift (or gain) of the…

Information Theory · Computer Science 2015-11-30 Radha K. Ganti , Martin Haenggi

We consider arbitrary dense wireless networks, in which $n$ nodes are placed in an arbitrary (deterministic) manner on a square region of unit area and communicate with each other over Gaussian fading channels. We provide inner and outer…

Information Theory · Computer Science 2011-08-09 Urs Niesen

We study the performance of wireless links for a class of Poisson networks, in which packets arrive at the transmitters following Bernoulli processes. By combining stochastic geometry with queueing theory, two fundamental measures are…

Information Theory · Computer Science 2020-07-22 Howard H. Yang , Tony Q. S. Quek , H. Vincent Poor

This work studies the signal-to-interference-plus-noise-ratio (SINR) meta distribution for the uplink transmission of a Poisson network with Rayleigh fading by using the dominant interferer-based approximation. The proposed approach relies…

Information Theory · Computer Science 2023-09-12 Yujie Qin , Mustafa A. Kishk , Mohamed-Slim Alouini

We define a new diffusive matrix model converging towards the $\beta$ -Dyson Brownian motion for all $\beta\in [0,2]$ that provides an explicit construction of $\beta$-ensembles of random matrices that is invariant under the…

Probability · Mathematics 2013-01-29 Romain Allez , Jean-Philippe Bouchaud , Alice Guionnet

This paper proposes a novel approach for computing the meta distribution of the signal-to-interference-plus-noise ratio (SINR) for the downlink transmission in a wireless network with Rayleigh fading. The novel approach relies on an…

Information Theory · Computer Science 2023-02-08 Yujie Qin , Mustafa A. Kishk , Mohamed-Slim Alouini

We consider the product of \(k_{n}\) independent \(n\times n\) complex Ginibre matrices and denote its eigenvalues by \(Z_{1},\ldots ,Z_{n}\). Let \(\alpha = \lim_{n\to\infty} n / k_{n}\). Using the determinantal point process method, we…

Probability · Mathematics 2026-04-16 Yutao Ma , Xujia Meng

This article studies the infinite-width limit of deep feedforward neural networks whose weights are dependent, and modelled via a mixture of Gaussian distributions. Each hidden node of the network is assigned a nonnegative random variable…

Machine Learning · Statistics 2025-02-06 Hoil Lee , Fadhel Ayed , Paul Jung , Juho Lee , Hongseok Yang , François Caron