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Collaborative Sensor Network Localization: Algorithms and Practical Issues

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TLDR
The state of the art in collaborative localization based on range-based as well as range-angle-based techniques is surveyed with an eye toward 5G cellular and IoT applications.
Abstract
Emerging communication network applications including fifth-generation (5G) cellular and the Internet-of-Things (IoT) will almost certainly require location information at as many network nodes as possible. Given the energy requirements and lack of indoor coverage of Global Positioning System (GPS), collaborative localization appears to be a powerful tool for such networks. In this paper, we survey the state of the art in collaborative localization with an eye toward 5G cellular and IoT applications. In particular, we discuss theoretical limits, algorithms, and practical challenges associated with collaborative localization based on range-based as well as range-angle-based techniques.

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Citations
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Non-line-of-sight node localization based on semi-definite programming in wireless sensor networks (アドホックネットワーク)

TL;DR: In this article, a semi-definite programming (SDP) based node localization algorithm in NLOS environments is proposed for ultra-wideband (UWB) wireless sensor networks, where the positions of sensors can be estimated using the distance estimates from location-aware anchors as well as other sensors.
Journal ArticleDOI

Soft Information for Localization-of-Things

TL;DR: The results show that SI-based localization is highly efficient, can significantly outperform classical techniques, and provides robustness to harsh propagation conditions.
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Harnessing NLOS Components for Position and Orientation Estimation in 5G Millimeter Wave MIMO

TL;DR: In this paper, the role of NLOS components for position and orientation estimation in 5G millimeter wave MIMO systems is investigated based on the concept of Fisher information, and it is shown that for sufficiently high temporal and spatial resolution, the NLOS component always provides position and orientations information that consequently increase position and position estimation accuracy.
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Reconfigurable Intelligent Surfaces: A signal processing perspective with wireless applications

TL;DR: In this paper , the authors provide a tutorial on the fundamental properties of the RIS technology from a signal processing perspective, and exemplify how they can be utilized for improved communication, localization, and sensing.
References
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Locating the nodes: cooperative localization in wireless sensor networks

TL;DR: Using the models, the authors have shown the calculation of a Cramer-Rao bound (CRB) on the location estimation precision possible for a given set of measurements in wireless sensor networks.

Range-Free Localization Schemes for Large Scale Sensor Networks 1

TL;DR: This paper presents APIT, a novel localization algorithm that is range-free, and shows that the APIT scheme performs best when an irregular radio pattern and random node placement are considered, and low communication overhead is desired.
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