Location Awareness in Beyond 5G Networks

Conti, Andrea; Morselli, Flavio; Liu, Zhenyu; Bartoletti, Stefania; Mazuelas, Santiago; Lindsey, W. C.; Win, Moe Z.

doi:10.1109/mcom.221.2100359

Cited by 50 publications

(33 citation statements)

References 12 publications

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“…New localization and tracking approaches within the context of 6G localization [7] take advantage of large measurement apertures as ultra wide band (UWB) systems [8], [9] or mmWave systems [10], which allow the received radio signal to be resolved into a superposition of a finite number of specular multipath components (MPCs) [8], [11]- [13]. Such For each base station j ∈ {1, ..., J} we observe a baseband radio signal signal vector r (j)…”

Section: A State-of-the-art Methodsmentioning

confidence: 99%

Graph-based Simultaneous Localization and Bias Tracking for Robust Positioning in Obstructed LOS Situations

Venus

Leitinger

Tertinek³

et al. 2022

2022 56th Asilomar Conference on Signals, Systems, and Computers

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This paper presents a neural-enhanced probabilistic model and corresponding factor graph-based sum-product algorithm for robust localization and tracking in multipathprone environments. The introduced hybrid probabilistic model consists of physics-based and data-driven measurement models capturing the information contained in both, the line-of-sight (LOS) component as well as in multipath components (NLOS components). The physics-based and data-driven models are embedded in a joint Bayesian framework allowing to derive from first principles a factor graph-based algorithm that fuses the information of these models. The proposed algorithm uses radio signal measurements from multiple base stations to robustly estimate the mobile agent's position together with all model parameters. It provides high localization accuracy by exploiting the position-related information of the LOS component via the physics-based model and robustness by exploiting the geometric imprint of multipath components independent of the propagation channel via the data-driven model. In a challenging numerical experiment involving obstructed LOS situations to all anchors, we show that the proposed sequential algorithm significantly outperforms state-of-the-art methods and attains the posterior Cramér-Rao lower bound even with training data limited to local regions.

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Section: A State-of-the-art Methodsmentioning

confidence: 99%

Graph-based Simultaneous Localization and Bias Tracking for Robust Positioning in Obstructed LOS Situations

Venus

Leitinger

Tertinek³

et al. 2022

2022 56th Asilomar Conference on Signals, Systems, and Computers

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show abstract

“…As discussed in Section 2, to keep the system stable, the amount of information that must flow through the feedback loop must compensate for the expansion in the uncertainty of the state, and this dictates the communication constraints expressed by the various data-rate theorem formulations. In the absence of the controller, the problem of estimating the state of an open-loop dynamical system observed over a communication channel is also of interest and is further motivated by additional applications, such as situation awareness (82)(83)(84), asset tracking (85-87), smart cities (88)(89)(90), the internet of things (91)(92)(93), and network localization and navigation (94)(95)(96)(97), where nodes in a network aim to infer their positions and possibly other position-related quantities using observations obtained via different types of sensors. In this case, results analogous to the data-rate theorem for stabilization have been obtained, and in what follows we wish to compare them and put them in the context of those that we have already described.…”

Section: Estimation Under Communication Constraintsmentioning

confidence: 99%

The Many Facets of Information in Networked Estimation and Control

Franceschetti

Khojasteh

Win

2023

Annu. Rev. Control Robot. Auton. Syst.

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Networked control systems, where feedback loops are closed over communication networks, arise in several domains, including smart energy grids, autonomous driving, unmanned aerial vehicles, and many industrial and robotic systems active in service, production, agriculture, and smart homes and cities. In these settings, the two main layers of the system, control and communication, strongly affect each other's performance, and they also reveal the interaction between a cyber-system component, represented by information-based computing and communication technologies, and a physical-system component, represented by the environment that needs to be controlled. The information access and distribution constraints required to achieve reliable state estimation and stabilization in networked control systems have been intensively studied over the course of roughly two decades. This article reviews some of the cornerstone results in this area, draws a map for what we have learned over these years, and describes the new challenges that we will face in the future. Rather than simply listing different results, we present them in a coherent fashion using a uniform notation, and we also put them in context, highlighting both their theoretical insights and their practical significance. Particular attention is given to recent developments related to decentralized estimation in distributed sensing and communication systems and the information-theoretic value of event timing in the context of networked control. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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“…L OCATION AWARENESS is crucial in fifth generation (5G) and beyond 5G (B5G) ecosystems [1], [2], [3], [4] to enable several applications and use cases, including intelligent transportation, public safety, and smart environments. Current 5G standardization supports localization of collaborative targets (e.g., people, vehicles, and objects) equipped with user equipments (UEs) or dedicated devices [1].…”

Section: Introductionmentioning

confidence: 99%

Device-Free Localization: Outdoor 5G Experimentation at mm-Waves

et al. 2023

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Device-free localization (DFL) will enable several use cases of fifth generation (5G) and beyond 5G (B5G) ecosystems that rely on position information of non-collaborative targets. While current 5G systems support device-based localization, their sensing capabilities for providing DFL have not been unleashed. This letter presents an experimentation and measurement campaign for outdoor device-free target detection and localization using as transmitter a 5G fixed wireless access at millimeter waves (mm-Waves), namely in the 28 GHz band. Specifically, the experimentation focuses on exploring the sensing capabilities of 5G systems to determine the positions of device-free targets. Experimental results show the potential of 5G DFL at mm-Waves.

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Location Awareness in Beyond 5G Networks

Cited by 50 publications

References 12 publications

Graph-based Simultaneous Localization and Bias Tracking for Robust Positioning in Obstructed LOS Situations

Graph-based Simultaneous Localization and Bias Tracking for Robust Positioning in Obstructed LOS Situations

The Many Facets of Information in Networked Estimation and Control

Device-Free Localization: Outdoor 5G Experimentation at mm-Waves

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