Journal ArticleDOI
Compressive Cooperative Sensing and Mapping in Mobile Networks
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TLDR
A new framework is proposed that allows the nodes to build a map of the parameter of interest with a small number of measurements and enables a novel non-invasive approach to mapping obstacles by using wireless channel measurements.Abstract:
In this paper, we consider a mobile cooperative network that is tasked with building a map of the spatial variations of a parameter of interest, such as an obstacle map or an aerial map. We propose a new framework that allows the nodes to build a map of the parameter of interest with a small number of measurements. By using the recent results in the area of compressive sensing, we show how the nodes can exploit the sparse representation of the parameter of interest in the transform domain in order to build a map with minimal sensing. The proposed work allows the nodes to efficiently map the areas that are not sensed directly. We consider three main areas essential to the cooperative operation of a mobile network: building a map of the spatial variations of a field of interest such as aerial mapping, mapping of the obstacles based on only wireless measurements, and mapping of the communication signal strength. For the case of obstacle mapping, we show how our framework enables a novel noninvasive mapping approach (without direct sensing), by using wireless channel measurements. Overall, our results demonstrate the potentials of this framework.read more
Citations
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Journal ArticleDOI
Random Access Compressed Sensing for Energy-Efficient Underwater Sensor Networks
TL;DR: The RACS scheme prolongs network life-time while employing a simple and distributed scheme which eliminates the need for scheduling, and is suitable for long-term deployment of large underwater networks.
Journal ArticleDOI
Breathfinding: A Wireless Network That Monitors and Locates Breathing in a Home
TL;DR: Using RSS measurements on the links between commercial wireless devices to locate where a breathing person is located and to estimate their breathing rate, in a home, while the person is sitting, lying down, standing, or sleeping is explored.
Journal ArticleDOI
Propagation Modeling for Radio Frequency Tomography in Wireless Networks
TL;DR: This paper designs an RF tomography testbed and describes the techniques used to conduct field test measurements, comparing both existing and novel shadowing models analytically, and presents the experimental results from the testbed comparing several differentshadowing models.
Journal ArticleDOI
Cooperative Wireless-Based Obstacle/Object Mapping and See-Through Capabilities in Robotic Networks
TL;DR: This paper develops a theoretical and experimental framework for the mapping of obstacles (including occluded ones), in a robotic cooperative network, based on a small number of wireless channel measurements, which would allow the robots to map an area before entering it.
Journal ArticleDOI
Robust Estimators for Variance-Based Device-Free Localization and Tracking
Yang Zhao,Neal Patwari +1 more
TL;DR: A new estimator, least squares variance-based radio tomography (LSVRT), is proposed, which reduces the impact of the variations caused by intrinsic motion and which achieves better localization accuracy and does not require manually tuning additional parameters compared to VRTI.
References
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Book
Convex Optimization
Stephen Boyd,Lieven Vandenberghe +1 more
TL;DR: In this article, the focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them, and a comprehensive introduction to the subject is given. But the focus of this book is not on the optimization problem itself, but on the problem of finding the appropriate technique to solve it.
Book
Compressed sensing
TL;DR: It is possible to design n=O(Nlog(m)) nonadaptive measurements allowing reconstruction with accuracy comparable to that attainable with direct knowledge of the N most important coefficients, and a good approximation to those N important coefficients is extracted from the n measurements by solving a linear program-Basis Pursuit in signal processing.
Journal ArticleDOI
Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
TL;DR: In this paper, the authors considered the model problem of reconstructing an object from incomplete frequency samples and showed that with probability at least 1-O(N/sup -M/), f can be reconstructed exactly as the solution to the lscr/sub 1/ minimization problem.
Book
Microwave Mobile Communications
William C. Jakes,Donald C. Cox +1 more
TL;DR: An in-depth and practical guide, Microwave Mobile Communications will provide you with a solid understanding of the microwave propagation techniques essential to the design of effective cellular systems.