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New large deviations results that characterize the asymptotic information rates for general $d$-dimensional ($d$-D) stationary Gaussian fields are obtained. By applying the general results to sensor nodes on a two-dimensional (2-D) lattice,…

Information Theory · Computer Science 2009-03-10 Youngchul Sung , H. Vincent Poor , Heejung Yu

The problem of optimal node density for ad hoc sensor networks deployed for making inferences about two dimensional correlated random fields is considered. Using a symmetric first order conditional autoregressive Gauss-Markov random field…

Information Theory · Computer Science 2016-11-17 Youngchul Sung , H. Vincent Poor , Heejung Yu

The detection of hidden two-dimensional Gauss-Markov random fields using sensor networks is considered. Under a conditional autoregressive model, the error exponent for the Neyman-Pearson detector satisfying a fixed level constraint is…

Information Theory · Computer Science 2016-11-15 Youngchul Sung , H. Vincent Poor , Heejung Yu

Distributed consensus has been widely studied for sensor network applications. Whereas the asymptotic convergence rate has been extensively explored in prior work, other important and practical issues, including energy efficiency and link…

Networking and Internet Architecture · Computer Science 2013-04-10 Lei Chen , Jeff Frolik

Wireless sensor networks are often designed to perform two tasks: sensing a physical field and transmitting the data to end-users. A crucial aspect of the design of a WSN is the minimization of the overall energy consumption. Previous…

Information Theory · Computer Science 2014-01-07 Zichong Chen , Juri Ranieri , Runwei Zhang , Martin Vetterli

The main objective of this paper is to reduce the number of sensor nodes by estimating a trade off between data accuracy and energy consumption for selecting nodes in probabilistic approach in distributed networks. Design…

Networking and Internet Architecture · Computer Science 2011-11-21 Jyotirmoy Karjee , H. S Jamadagni

We study the large deviations performance, i.e., the exponential decay rate of the error probability, of distributed detection algorithms over random networks. At each time step $k$ each sensor: 1) averages its decision variable with the…

Information Theory · Computer Science 2010-12-22 Dragana Bajovic , Dusan Jakovetic , Joao Xavier , Bruno Sinopoli , Jose M. F. Moura

In this paper, we consider a point-to-point link between an energy harvesting transmitter and receiver, where neither node has the information about the battery state or energy availability at the other node. We consider a model where data…

Information Theory · Computer Science 2017-06-15 Mohit K. Sharma , Chandra R. Murthy , Rahul Vaze

As large-scale dense and often randomly deployed wireless sensor networks (WSNs) become widespread, local information exchange between co-located sets of nodes may play a significant role in handling the excessive traffic volume. Moreover,…

Ad hoc network is a collection of different types of nodes, which are connected in heterogeneous or homogeneous manner. It is also known as self-organizing-wireless network. The dynamic nature of ad hoc networks make them more attractive,…

Networking and Internet Architecture · Computer Science 2020-04-15 Priya P. Patel , Rutvij H. Jhaveri

The problem of decentralized detection in a sensor network subjected to a total average power constraint and all nodes sharing a common bandwidth is investigated. The bandwidth constraint is taken into account by assuming non-orthogonal…

Information Theory · Computer Science 2007-07-13 Sudharman K. Jayaweera

The aim of this work is to model the nodes battery discharge in wireless ad hoc networks. Many work focus on the energy consumption in such networks. Even, the research in the highest layers of the ISO model, takes into account the energy…

Networking and Internet Architecture · Computer Science 2012-06-08 Maher Heni , Ammar Bouallegue , Ridha Bouallegue

Energy harvesting (EH) from ambient radio-frequency (RF) electromagnetic waves is an efficient solution for fully autonomous and sustainable communication networks. Most of the related works presented in the literature are based on specific…

Information Theory · Computer Science 2016-11-18 Ioannis Krikidis

Based on stochastic differential equations (SDEs), we analyse the overall performance of heterogeneous power systems network, subject to spatially distributed and correlated noise with random initial conditions. We determine bounds on the…

Optimization and Control · Mathematics 2021-11-22 Taouba Jouini , Zhiyong Sun

This paper characterizes and jointly optimizes Age of Information (AoI) and energy efficiency in heterogeneous correlated random access networks, where each sensor adopts a distinct transmission probability and its observations are…

Networking and Internet Architecture · Computer Science 2025-09-09 Anshan Yuan , Xinghua Sun , Yayu Gao , Wen Zhan , Xiang Chen

In a series of two papers, we investigate the large deviations and asymptotic behavior of stochastic models of brain neural networks with random interaction coefficients. In this first paper, we take into account the spatial structure of…

Probability · Mathematics 2017-01-05 Tanguy Cabana , Jonathan Touboul

The performance of a dual-hop MIMO relay network is studied in this paper. The relay is assumed to have access to the statistical channel state information of its preceding and following channels and it is assumed that fading at the…

Information Theory · Computer Science 2015-05-26 Mehdi M. Molu , Alister Burr , Norbert Goertz

Intensive research on energy harvested sensor nodes with traditional battery powered devices has been driven by the challenges in achieving the stringent design goals of battery lifetime, information accuracy, transmission distance, and…

Networking and Internet Architecture · Computer Science 2021-07-16 Shitij Avlani , Donghyun Seo , Baibhab Chatterjee , Shreyas Sen

State estimation is required whenever we deal with high-dimensional dynamical systems, as the complete measurement is often unavailable. It is key to gaining insight, performing control or optimizing design tasks. Most deep learning-based…

Machine Learning · Computer Science 2022-03-15 Yash Kumar , Souvik Chakraborty

During a spontaneous change, a macroscopic physical system will evolve towards a macro-state with more realizations. This observation is at the basis of the Statistical Mechanical version of the Second Law of Thermodynamics, and it provides…

Statistical Mechanics · Physics 2020-04-22 Mengjie Zu , Arunkumar Bupathy , Daan Frenkel , Srikanth Sastry
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