3GPP-Compliant Datasets for xG Location-Aware Networks
Location awareness is vital in next generation (xG) wireless networks to enable different use cases, including location-based services (LBSs) and efficient network management. However, achieving the service level requirements specified by the 3rd Generation Partnership Project (3GPP) is challenging....
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
|
| Series: | IEEE Open Journal of Vehicular Technology |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10349917/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832582297916801024 |
|---|---|
| author | Andrea Conti Gianluca Torsoli Carlos A. Gomez-Vega Alessandro Vaccari Gianluca Mazzini Moe Z. Win |
| author_facet | Andrea Conti Gianluca Torsoli Carlos A. Gomez-Vega Alessandro Vaccari Gianluca Mazzini Moe Z. Win |
| author_sort | Andrea Conti |
| collection | DOAJ |
| description | Location awareness is vital in next generation (xG) wireless networks to enable different use cases, including location-based services (LBSs) and efficient network management. However, achieving the service level requirements specified by the 3rd Generation Partnership Project (3GPP) is challenging. This calls for new localization algorithms as well as for 3GPP-standardized scenarios to support their systematic development and testing. In this context, the availability of public datasets with 3GPP-compliant configurations is essential to advance the evolution of xG networks. This paper introduces xG-Loc, the first open dataset for localization algorithms and services fully compliant with 3GPP technical reports and specifications. xG-Loc includes received localization signals, measurements, and analytics for different network and signal configurations in indoor and outdoor scenarios with center frequencies from micro-waves in frequency range 1 (FR1) to millimeter-waves in frequency range 2 (FR2). Position estimates obtained via soft information-based localization and wireless channel quality indicators via blockage intelligence are also provided. The rich set of data provided by xG-Loc enables the characterization of localization algorithms and services under common 3GPP-standardized scenarios in xG networks. |
| format | Article |
| id | doaj-art-43d7f6c4b15f43eb9689431010c77822 |
| institution | Kabale University |
| issn | 2644-1330 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Vehicular Technology |
| spelling | doaj-art-43d7f6c4b15f43eb9689431010c778222025-01-30T00:04:26ZengIEEEIEEE Open Journal of Vehicular Technology2644-13302024-01-01547348410.1109/OJVT.2023.3340993103499173GPP-Compliant Datasets for xG Location-Aware NetworksAndrea Conti0https://orcid.org/0000-0001-9224-2178Gianluca Torsoli1https://orcid.org/0009-0002-4460-2882Carlos A. Gomez-Vega2https://orcid.org/0000-0002-6670-1294Alessandro Vaccari3https://orcid.org/0000-0001-9135-9155Gianluca Mazzini4https://orcid.org/0000-0003-3867-760XMoe Z. Win5https://orcid.org/0000-0002-8573-0488Department of Engineering and CNIT, University of Ferrara, Ferrara, ItalyDepartment of Engineering and CNIT, University of Ferrara, Ferrara, ItalyDepartment of Engineering and CNIT, University of Ferrara, Ferrara, ItalyDepartment of Engineering and CNIT, University of Ferrara, Ferrara, ItalyDepartment of Engineering and CNIT, University of Ferrara, Ferrara, ItalyLaboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA, USALocation awareness is vital in next generation (xG) wireless networks to enable different use cases, including location-based services (LBSs) and efficient network management. However, achieving the service level requirements specified by the 3rd Generation Partnership Project (3GPP) is challenging. This calls for new localization algorithms as well as for 3GPP-standardized scenarios to support their systematic development and testing. In this context, the availability of public datasets with 3GPP-compliant configurations is essential to advance the evolution of xG networks. This paper introduces xG-Loc, the first open dataset for localization algorithms and services fully compliant with 3GPP technical reports and specifications. xG-Loc includes received localization signals, measurements, and analytics for different network and signal configurations in indoor and outdoor scenarios with center frequencies from micro-waves in frequency range 1 (FR1) to millimeter-waves in frequency range 2 (FR2). Position estimates obtained via soft information-based localization and wireless channel quality indicators via blockage intelligence are also provided. The rich set of data provided by xG-Loc enables the characterization of localization algorithms and services under common 3GPP-standardized scenarios in xG networks.https://ieeexplore.ieee.org/document/10349917/3GPPxGlocalizationdatasetnext-generation networks |
| spellingShingle | Andrea Conti Gianluca Torsoli Carlos A. Gomez-Vega Alessandro Vaccari Gianluca Mazzini Moe Z. Win 3GPP-Compliant Datasets for xG Location-Aware Networks IEEE Open Journal of Vehicular Technology 3GPP xG localization dataset next-generation networks |
| title | 3GPP-Compliant Datasets for xG Location-Aware Networks |
| title_full | 3GPP-Compliant Datasets for xG Location-Aware Networks |
| title_fullStr | 3GPP-Compliant Datasets for xG Location-Aware Networks |
| title_full_unstemmed | 3GPP-Compliant Datasets for xG Location-Aware Networks |
| title_short | 3GPP-Compliant Datasets for xG Location-Aware Networks |
| title_sort | 3gpp compliant datasets for xg location aware networks |
| topic | 3GPP xG localization dataset next-generation networks |
| url | https://ieeexplore.ieee.org/document/10349917/ |
| work_keys_str_mv | AT andreaconti 3gppcompliantdatasetsforxglocationawarenetworks AT gianlucatorsoli 3gppcompliantdatasetsforxglocationawarenetworks AT carlosagomezvega 3gppcompliantdatasetsforxglocationawarenetworks AT alessandrovaccari 3gppcompliantdatasetsforxglocationawarenetworks AT gianlucamazzini 3gppcompliantdatasetsforxglocationawarenetworks AT moezwin 3gppcompliantdatasetsforxglocationawarenetworks |