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- Savelli, Marco, et al.
(författare)
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Range-Free Positioning in NB-IoT Networks by Machine Learning
- 2024
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Ingår i: Conference Proceedings-2024 International Conference on Localization and GNSS, ICL-GNSS. - : Institute of Electrical and Electronics Engineers (IEEE). - 9798350380798 - 9798350380781
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Konferensbidrag (refereegranskat)abstract
- Existing proposals for positioning in NB-IoT networks based on range estimation are characterized by either low accuracy or lack of compliance with 3GPP standards. While range-free approaches taking advantage of Machine Learning (ML) have been recently proposed as a potential way forward, their evaluation has been carried out only in simulated environments, with the exception of Weighted k Nearest Neighbours (WkNN), recently tested on experimental data. This work inves-tigates four ML strategies for range-free positioning in NB-IoT networks, based on WkNN and its combination with preprocessing and classification algorithms as well as on Artificial Neural Networks (ANNs). The strategies are evaluated on experimental data and are compared based on a set of Key Performance Indicators (KPIs) measuring both positioning performance and computational complexity. Results show that range-free positioning using ML is a viable solution in commercial NB-IoT networks, and that WkNN and ANNs are at the two extremes in terms of a performance/complexity trade-off; intermediate trade-offs can be achieved by combining WkNN with preprocessing techniques and classification models.
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| 6. |
- Ali, Usman, et al.
(författare)
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Data-Driven Analysis of Outdoor-to-Indoor Propagation for 5G Mid-Band Operational Networks
- 2022
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Ingår i: Future Internet. - : MDPI. - 1999-5903. ; 14:8, s. 1-27
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Tidskriftsartikel (refereegranskat)abstract
- The successful rollout of fifth-generation (5G) networks requires a full understanding of the behavior of the propagation channel, taking into account the signal formats and the frequencies standardized by the Third Generation Partnership Project (3GPP). In the past, channel characterization for 5G has been addressed mainly based on the measurements performed on dedicated links in experimental setups. This paper presents a state-of-the-art contribution to the characterization of the outdoor-to-indoor radio channel in the 3.5 GHz band, based on experimental data for commercial, deployed 5G networks, collected during a large scale measurement campaign carried out in the city of Rome, Italy. The analysis presented in this work focuses on downlink, outdoor-to-indoor propagation for two operators adopting two different beamforming strategies, single wide-beam and multiple synchronization signal blocks (SSB) based beamforming; it is indeed the first contribution studying the impact of beamforming strategy in real 5G networks. The time and power-related channel characteristics, i.e., mean excess delay and Root Mean Square (RMS) delay spread, path loss, and K-factor are studied for the two operators in multiple measurement locations. The analysis of time and power-related parameters is supported and extended by a correlation analysis between each pair of parameters. The results show that beamforming strategy has a marked impact on propagation. A single wide-beam transmission leads, in fact, to lower RMS delay spread and lower mean excess delay compared to a multiple SSB-based transmission strategy. In addition, the single wide-beam transmission system is characterized by a smaller path loss and a higher K-factor, suggesting that the adoption of a multiple SSB-based transmission strategy may have a negative impact on downlink performance.
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| 7. |
- Ali, Usman, et al.
(författare)
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Large-Scale Dataset for the Analysis of Outdoor-to-Indoor Propagation for 5G Mid-Band Operational Networks
- 2022
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Ingår i: Data. - : MDPI. - 2306-5729. ; 7:3, s. 34-34
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Tidskriftsartikel (refereegranskat)abstract
- Understanding radio propagation characteristics and developing channel models is fundamental to building and operating wireless communication systems. Among others uses, channel characterization and modeling can be used for coverage and performance analysis and prediction. Within this context, this paper describes a comprehensive dataset of channel measurements performed to analyze outdoor-to-indoor propagation characteristics in the mid-band spectrum identified for the operation of 5th Generation (5G) cellular systems. Previous efforts to analyze outdoor-to-indoor propagation characteristics in this band were made by using measurements collected on dedicated, mostly single-link setups. Hence, measurements performed on deployed and operational 5G networks still lack in the literature. To fill this gap, this paper presents a dataset of measurements performed over commercial 5G networks. In particular, the dataset includes measurements of channel power delay profiles from two 5G networks in Band n78, i.e., 3.3–3.8 GHz. Such measurements were collected at multiple locations in a large office building in the city of Rome, Italy by using the Rohde & Schwarz (R&S) TSMA6 network scanner during several weeks in 2020 and 2021. A primary goal of the dataset is to provide an opportunity for researchers to investigate a large set of 5G channel measurements, aiming at analyzing the corresponding propagation characteristics toward the definition and refinement of empirical channel propagation models.
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| 8. |
- Armiero, Marco, et al.
(författare)
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Political History and Environmental History in Italy
- 2018
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Ingår i: Ricerche di Storia Politica. - : Societa Editrice Il Mulino. - 1120-9526. ; 21:1, s. 63-73
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Tidskriftsartikel (refereegranskat)abstract
- Environmental history has grown greatly in various countries, in the last years, and has penetrated in Italy, too. At the same time, it remains in many ways a small sector, while political history, for its part, seems to be untouched by it, despite the relevance of the environment in political discourse. The forum, which closes this special issue on the relationship between politics and the environment, and involves both environmental and political historians, intends to give a contribution to the debate on the nature and fate of political and, more generally, contemporary history.
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| 9. |
- Caso, Giuseppe, et al.
(författare)
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An Initial Look into the Performance Evolution of 5G Non-Standalone Networks
- 2023
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Ingår i: TMA 2023 - Proceedings of the 7th Network Traffic Measurement and Analysis Conference. - : Institute of Electrical and Electronics Engineers (IEEE). - 9798350325676 - 9783903176584 ; , s. 1-4
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Konferensbidrag (refereegranskat)abstract
- Fifth Generation (5G) networks have been operational worldwide for a couple of years. To reveal how the 5G system evolution (e.g., changes in network conditions, deployment, and configurations) affects user performance, empirical long-term analyses are required. This paper presents preliminary insights from our ongoing large-scale measurement study of the commercial 5G non-standalone (NSA) networks deployed in Rome, Italy. An initial comparison between the measurements in 2020-2021 vs. 2023 shows a decrease in throughput and latency performance, calling for deeper analyses toward understanding the root causes and deriving proper optimization solutions.
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| 10. |
- Caso, Giuseppe, et al.
(författare)
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Empirical Models for NB-IoT Path Loss in an Urban Scenario
- 2021
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 8:17, s. 13774-13788
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Tidskriftsartikel (refereegranskat)abstract
- The lack of publicly available large scale measurements has hindered the derivation of empirical path loss (PL) models for Narrowband Internet of Things (NB-IoT). Therefore, simulation-based investigations currently rely on models conceived for other cellular technologies, which are characterized, however, by different available bandwidth, carrier frequency, and infrastructure deployment, among others. In this paper, we take advantage of data from a large scale measurement campaign in the city of Oslo, Norway, to provide the first empirical characterization of NB-IoT PL in an urban scenario. For the PL average term, we characterize Alpha-Beta-Gamma (ABG) and Close-In (CI) models. By analyzing multiple NBIoT cells, we propose a statistical PL characterization, i.e., the model parameters are not set to a single, constant value across cells, but are randomly extracted from well-known distributions. Similarly, we define the PL shadowing distribution, correlation over distance, and inter-site correlation. Finally, we give initial insights on outdoor-to-indoor propagation, using measurements up to deep indoor scenarios. The proposed models improve PL estimation accuracy compared to the ones currently adopted in NB-IoT investigations, enabling more realistic simulations of urban scenarios similar to the sites covered by our measurements.
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