Network Operation Strategies for Efficient Localization and Navigation

Win, Moe Z.; Dai, Wenhan; Shen, Yuan; Chrisikos, G.; Poor, H. Vincent

doi:10.1109/jproc.2018.2835314

Cited by 141 publications

(54 citation statements)

References 138 publications

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“…The localization problem has been extensively explored in the literature for various kind of networks in different scenarios [12]- [16]. However, the new characteristics of IoT networks, such as the long-range, limited number of messages, and the inexpensive IoT nodes, bring extra localization challenges.…”

Section: A Related Workmentioning

confidence: 99%

Localization in Ultra Narrow Band IoT Networks: Design Guidelines and Tradeoffs

Sallouha

Chiumento

Rajendran

et al. 2019

IEEE Internet Things J.

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Localization in long-range Internet of Things networks is a challenging task, mainly due to the long distances and low bandwidth used. Moreover, the cost, power, and size limitations restrict the integration of a GPS receiver in each device. In this work, we introduce a novel received signal strength indicator (RSSI) based localization solution for ultra narrow band (UNB) long-range IoT networks such as Sigfox. The essence of our approach is to leverage the existence of a few GPSenabled sensors (GSNs) in the network to split the wide coverage into classes, enabling RSSI based fingerprinting of other sensors (SNs). By using machine learning algorithms at the network backed-end, the proposed approach does not impose extra power, payload, or hardware requirements. To comprehensively validate the performance of the proposed method, a measurement-based dataset that has been collected in the city of Antwerp is used. We show that a location classification accuracy of 80% is achieved by virtually splitting a city with a radius of 2.5 km into seven classes. Moreover, separating classes, by increasing the spacing between them, brings the classification accuracy up-to 92% based on our measurements. Furthermore, when the density of GSN nodes is high enough to enable device-to-device communication, using multilateration, we improve the probability of localizing SNs with an error lower than 20 m by 40% in our measurement scenario.

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Section: A Related Workmentioning

confidence: 99%

Localization in Ultra Narrow Band IoT Networks: Design Guidelines and Tradeoffs

Sallouha

Chiumento

Rajendran

et al. 2019

IEEE Internet Things J.

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show abstract

“…Furthermore, the mobility of vehicular UE, prior location knowledge, the number of LEDs, prior UE location knowledge and signal-to-noise-ratio (SNR) will also affect the VLP performance. Hence, it is non-trivial to reveal the RSS-based VLP performance limits for vehicular UEs, which is indispensable for designing a location-aware IOV network and system resource allocation [22], as done in [23]- [27] for wideband system optimization.…”

Section: Introductionmentioning

confidence: 99%

Performance Limits of Visible Light-Based Positioning for Internet-of-Vehicles: Time-Domain Localization Cooperation Gain

Zhou

Liu

Lau

et al. 2021

IEEE Trans. Intell. Transport. Syst.

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In this paper, we aim to give a unified performance limit analysis of the visible light-based positioning (VLP) for a vehicular user equipment (UE), which will help to understand the essence of time-domain localization cooperation and gain insights into how to improve the performance of the vehicular VLP system. This is not easy due to the complex system models and the complicated dependency between UE location performance and orientation performance. To achieve the above goal, we will first characterize the closed-form error bounds of the UE location and orientation at each time slot, respectively, in terms of Fisher information. Generally, the VLP error will propagate over time as the vehicular UE moves, and hence the VLP error at the current time slot is affected by the VLP performance at the previous time slot, the UE mobility and the channel quality. Based on the obtained VLP error bounds, we then reveal the impact of prior UE location knowledge, UE mobility and signal-to-noise-ratio on the VLP performance. Furthermore, the time-domain evolution of the VLP error is studied, where the convergence of the timedomain VLP error evolution is established and its closed-form stable state is quantified, which will shed light on the long-term performance of the vehicular VLP system.

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“…Location-awareness technologies play an important role in many applications, such as logistics, autonomous vehicles, medical care, and smart factories [1][2][3][4]. The Global Navigation Satellite System (GNSS) is the most common position service provider, while its accuracy is affected by urban multipath components (MPCs) and non-line-of-sight (NLOS) propagations in indoor environments.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Single-Anchor Localization Method Using Ultra-Wide Bandwidth Systems

2019

Self Cite

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Ultra-wideband technology has the merits of high temporal resolution and stability, and it has been widely used for high-accuracy localization and tracking. However, most ultra-wideband localization systems need multiple anchors for trilateration, which results in high system cost, large messages overhead, and insufficient extraction of information. In this paper, we propose a single-anchor localization (SAL) mehtod that achieves high-accuracy multi-agent localization with high efficiency. In the proposed method, the anchor broadcasts the first two messages and then each agent responds one message to the anchor (quasi-)simultaneously. Based on the received message with superpositioned agent responses, the time-of-flight and angle-of-arrival information from all agents to the anchor can be extracted altogether. We implement the localization system in two indoor environments, and show that the proposed method can achieve decimeter-level accuracy for multiple agents using three messages. Our method provides design guidelines for high-accuracy and high-efficiency multi-agent localization systems.

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Network Operation Strategies for Efficient Localization and Navigation

Cited by 141 publications

References 138 publications

Localization in Ultra Narrow Band IoT Networks: Design Guidelines and Tradeoffs

Localization in Ultra Narrow Band IoT Networks: Design Guidelines and Tradeoffs

Performance Limits of Visible Light-Based Positioning for Internet-of-Vehicles: Time-Domain Localization Cooperation Gain

An Efficient Single-Anchor Localization Method Using Ultra-Wide Bandwidth Systems

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