The Internet of Things

Liberg, Olof; Sundberg, Mårten; Wang, Y.-P. Eric; Bergman, Johan; Sachs, Joachim; Wikström, Gustav

doi:10.1016/b978-0-08-102902-2.00001-7

Cited by 8 publications

(10 citation statements)

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“…Therefore, experiments were carried out that only preserved the N NPCI strongest/best NPCIs in points to be labeled as TPs; no change was made to data points labeled as RPs. Figure 12 shows the minimum average positioning error for all the proposed strategies as a function of N NPCI in the range [1,9]. The results show that, for all strategies, the positioning error decreases as the number of NPCIs used for each TP increases; in all cases, the error is close (within <2%) to the one obtained using all NPCIs (see Table 3) if at least 7 best NPCIs are used.…”

mentioning

confidence: 79%

“…The best results were obtained with the Pearson χ 2 coefficient as the similarity metric, with an average positioning error of about 184 m. Due to limitations in the hardware used to collect data, the fingerprints defined in [7] only included the RSSI of the cell to which the NB-IoT device was connected and thus only included information on a single cell. However, because of cell (re)selection purposes, the NB-IoT standard foresees that a device may collect data on multiple cells at the same time, similarly to what is commonly done by WiFi and LTE devices [1]. In areas characterized by high spatial network density, this may result in a large number of data elements being stored in each fingerprint.…”

Section: Background and Related Workmentioning

confidence: 99%

“…The error was then averaged over all the TPs and all the runs, leading to the average positioning error, which was adopted as the first performance indicator in the subsequent subsections. The average positioning error was measured for k varying in the range [1,40]; the minimum of the average positioning error as a function of k is referred to in the following as minimum average positioning error.…”

Section: Experiments Setup and Settingsmentioning

confidence: 99%

“…Minimum average positioning error and corresponding optimal k for the proposed strategies and the single cell approach in [7] using the Oslo dataset. Figure 9 presents the average positioning error as a function of k in the range [1,10] for all strategies, using SINR for the strategies taking advantage of RF information. The results show that the Enhanced Net, Coverage, and Weighted Coverage strategies provide consistently better accuracy than did Net and Single Cell for all k values.…”

Section: Impact Of Strategies and Rf Parametersmentioning

confidence: 99%

“…Narrowband Internet of Things (NB-IoT) is a leading technology in the context of low-power wide area networks (LPWANs), standardized by the 3rd Generation Partnership Project (3GPP) in Release 13 (Rel- 13,2016) and aimed at enabling low-cost and powerefficient IoT services over cellular networks [1]. Most of these services either require or benefit from location information [2].…”

Section: Introductionmentioning

confidence: 99%

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Positioning by Multicell Fingerprinting in Urban NB-IoT Networks

Nardis

Caso

Alay

et al. 2023

Sensors

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Narrowband Internet of Things (NB-IoT) has quickly become a leading technology in the deployment of IoT systems and services, owing to its appealing features in terms of coverage and energy efficiency, as well as compatibility with existing mobile networks. Increasingly, IoT services and applications require location information to be paired with data collected by devices; NB-IoT still lacks, however, reliable positioning methods. Time-based techniques inherited from long-term evolution (LTE) are not yet widely available in existing networks and are expected to perform poorly on NB-IoT signals due to their narrow bandwidth. This investigation proposes a set of strategies for NB-IoT positioning based on fingerprinting that use coverage and radio information from multiple cells. The proposed strategies were evaluated on two large-scale datasets made available under an open-source license that include experimental data from multiple NB-IoT operators in two large cities: Oslo, Norway, and Rome, Italy. Results showed that the proposed strategies, using a combination of coverage and radio information from multiple cells, outperform current state-of-the-art approaches based on single cell fingerprinting, with a minimum average positioning error of about 20 m when using data for a single operator that was consistent across the two datasets vs. about 70 m for the current state-of-the-art approaches. The combination of data from multiple operators and data smoothing further improved positioning accuracy, leading to a minimum average positioning error below 15 m in both urban environments.

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confidence: 79%

Section: Background and Related Workmentioning

confidence: 99%

Section: Experiments Setup and Settingsmentioning

confidence: 99%

Section: Impact Of Strategies and Rf Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Positioning by Multicell Fingerprinting in Urban NB-IoT Networks

Nardis

Caso

Alay

et al. 2023

Sensors

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Introduction and Scope

Heins¹

2022

Trusted Cellular IoT Devices

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Toward Deterministic Communications in 6G Networks: State of the Art, Open Challenges and the Way Forward

Sharma,

Patel,

Sachs

et al. 2023

IEEE Access

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Over the last decade, society and industries are undergoing rapid digitization that is expected to lead to the evolution of the cyber-physical continuum. End-to-end deterministic communications infrastructure is the essential glue that will bridge the digital and physical worlds of the continuum. We describe the state of the art and open challenges with respect to contemporary deterministic communications and compute technologies-3GPP 5G, IEEE Time-Sensitive Networking, IETF DetNet, OPC UA as well as edge computing. While these technologies represent significant technological advancements towards networking Cyber-Physical Systems (CPS), we argue in this paper that they rather represent a first generation of systems which are still limited in different dimensions. In contrast, realizing future deterministic communications systems requires, firstly, seamless convergence between these technologies and, secondly, scalability to support heterogeneous (time-varying requirements) arising from diverse CPS applications. In addition, future deterministic communication networks will have to provide such characteristics end-to-end, which for CPS refers to the entire communication and computation loop, from sensors to actuators. In this paper, we discuss the state of the art regarding the main challenges towards these goals: predictability, endto-end technology integration, end-to-end security, and scalable vertical application interfacing. We then present our vision regarding viable approaches and technological enablers to overcome these four central challenges. In particular, we argue that there is currently a window of opportunity to establish, through 6G standardization, the foundations towards a scalable and converged deterministic communications and compute infrastructure. Key approaches to leverage in that regard are 6G system evolutions, wireless-friendly 6G integration with TSN and DetNet, novel end-to-end security approaches, efficient edge-cloud integrations, data-driven approaches for stochastic characterization and prediction, as well as leveraging digital twins towards system awareness.

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The Internet of Things

Cited by 8 publications

References 0 publications

Positioning by Multicell Fingerprinting in Urban NB-IoT Networks

Positioning by Multicell Fingerprinting in Urban NB-IoT Networks

Introduction and Scope

Toward Deterministic Communications in 6G Networks: State of the Art, Open Challenges and the Way Forward

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