A GNSS–Cellular Network Hybridization Strategy for Robust Positioning
Source abstract
Abstract
The hybridization of cellular networks and GNSS systems has gained increasing attention, especially in urban canyons and indoor environments where GNSS performance degrades significantly. Hybrid localization is part of the 3rd Generation Partnership Project (3GPP) standard, offering an effective solution when satellite visibility is limited. Additional cellular measurements can enhance the accuracy and reliability of standalone UE. Hybrid methods offer multiple benefits: an improved availability, continuity, and integrity; better signal penetration due to proximity; a lower power consumption; and, in harsh environments, potentially more accurate positioning than a GNSS. Moreover, GNSS chipsets in mobile phones or smartwatches are typically power-intensive. This work presents a user-level hybridization method that enables UE to receive both GNSS and 4G/5G data and autonomously determine whether to apply hybrid positioning. The developed algorithms improve the precision and reliability, allowing user-driven decisions based on data quality. The system was tested under static conditions across various scenarios: outdoors, in urban canyons, and indoors. The results show that, while hybridization enhances positioning, the 4G-only solution often performs in terms of vertical accuracy. Standard deviation metrics help guide the selection of the most precise option in real time.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Indoor and Outdoor Localization Technologies · Wireless Communication Networks Research · Radio Wave Propagation Studies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Cartographic, Geodesy and Photogrammetry Engineering, Higher Technical School of Geodetic, Cartographic and Topographical Engineering, Universitat Politècnica de València, Campus de Vera s/n, 46022 Valencia, Spain
Telecommunications Engineering School, Faculty of Computer Science and Electronics, Escuela Superior Politécnica de Chimborazo (ESPOCH), Campus Chimborazo, Riobamba EC060155, Ecuador
References (40)
Show source-provided references
1. Gill, S. (2025, May 15). How Many People Own Smartphones in the World? (2024–2029). Available online: https://prioridata.com/data/smartphone-stats/.
2. Resilient Societies (2024). EUSPA EO and GNSS, Market Report, European Union Agency for the Space Programme (EUSPA).
3. GSMA (2025). The Mobile Economy 2025, GSM Association. Available online: https://www.gsma.com/solutions-and-impact/connectivity-for-good/mobile-economy/wp-content/uploads/2025/02/030325-The-Mobile-Economy-2025.pdf.
4. Federal Communications Commission (FCC) (2025, May 02). Available online: https://www.fcc.gov/.
5. 3GPP (2025, May 01). Introducing 3GPP. Available online: https://www.3gpp.org/about-us/introducing-3gpp.
6. FCC (2025, February 01). FCC & Wireless Communications and Public Safety Act of 1999, Available online: https://www.congress.gov/bill/106th-congress/house-bill/438.
7. FCC (2025, April 27). FCC Wireless E911 Location Accuracy Requirements, Fourth Report and Order, Available online: https://www.fcc.gov/document/fcc-adopts-new-wireless-indoor-e911-location-accuracy-requirements.
8. 3GPP (2025, May 15). 3GPP TS 23.271, Functional Stage 2 Description of Location Services (LCS), V9.4.0. Available online: https://portal.3gpp.org/desktopmodules/Specifications/SpecificationDetails.aspx?specificationId=834.
9. Positioning in 5G Networks10.1109/MCOM.011.2100091 ↗
10. 3GPP (2025, May 30). TS 36.305 V17.1.0, LTE; Evolved Universal Terrestrial Radio Access Network (E-UTRAN); Stage 2 Functional Specification of User Equipment (UE) Positioning in E-UTRAN. Available online: https://www.etsi.org/deliver/etsi_ts/136300_136399/136305/17.01.00_60/ts_136305v170100p.pdf.
11. García, A.C., Maier, S., and Phillips, A. (2020). Location-Based Services in Cellular Networks: From GSM to 5G NR, Artech House.
12. Groves, P.D. (2013). Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems, Artech House. [2nd ed.].
13. Del Peral-Rosado, J.A., Estatuet i Castillo, R., Mıguez-Sanchez, J., Navarro-Gallardo, M., García-Molina, J.A., López-Salcedo, J.A., Seco-Granados, G., Zanier, F., and Crisci, M. (2016, January 14–16). Performance Analysis of Hybrid GNSS and LTE Localization in Urban Scenarios. Proceedings of the 8th ESA Workshop on Satellite Navigation Technologies and European Workshop on GNSS Signals and Signal Processing (NAVITEC), Noordwijk, The Netherlands.10.1109/NAVITEC.2016.7849332 ↗
14. Alghisi, M., and Biagi, L. (2023). Positioning with GNSS and 5G: Analysis of Geometric Accuracy in Urban Scenarios. Sensors, 23.10.3390/s23042181 ↗
15. Dethroning GPS: Low-Power Accurate 5G Positioning Systems Using Machine Learning10.1109/JETCAS.2020.2991024 ↗
16. Del Peral-Rosado, J.A., Saloranta, J., Destino, G., López-Salcedo, J.A., and Seco-Granados, G. (2018). Methodology for simulating 5G and GNSS high-accuracy positioning. Sensors, 18.10.3390/s18103220 ↗
17. Del Peral-Rosado, J.A., Nolle, P., Razavi, S.M., Lindmark, G., Shrestha, D., Gunnarsson, F., Kaltenberger, F., Sirola, N., Särkkä, O., and Roström, J. (2022, January 5–7). Design Considerations of Dedicated and Aerial 5G Networks for Enhanced Positioning Services. Proceedings of the 10th Workshop on Satellite Navigation Technology, NAVITEC, Noordwijk, The Netherlands.10.1109/NAVITEC53682.2022.9847557 ↗
18. Van Diggelen, F. (2009). A-GPS: Assisted GPS, GNSS, and SBAS, Artech.
19. Xhafa, A., del Peral-Rosado, J.A., López-Salcedo, J.A., and Seco-Granados, G. (2022). Evaluation of 5G Positioning Performance Based on UTDoA, AoA and Base-Station Selective Exclusion. Sensors, 22.10.3390/s22010101 ↗
20. Liu, J., Deng, Z., Hu, E., Huang, Y., Deng, X., Zhang, Z., Ding, Z., and Liu, B. (2023). GNSS-5G Hybrid Positioning Based on Joint Estimation of Multiple Signals in a Highly Dependable Spatio-Temporal Network. Remote Sens., 15.10.3390/rs15174220 ↗
21. Duong, P.B., Ghimire, B., Dietmayer, K., Ali, S.U., Al Kim, H., and Seitz, J. (2022, January 5–8). Supervised Machine Learning Assisted Hybrid Positioning based on GNSS and 5G. Proceedings of the 2022 IEEE 12th International Conference on Indoor Positioning and Indoor Navigation (IPIN), Beijing, China.10.1109/IPIN54987.2022.9918098 ↗
22. Toward 5G NR High-Precision Indoor Positioning via Channel Frequency Response: A New Paradigm and Dataset Generation Method10.1109/JSAC.2022.3157397 ↗
23. Survey of Cellular Mobile Radio Localization Methods: From 1G to 5G10.1109/COMST.2017.2785181 ↗
24. An Adaptive IMU/UWB Fusion Method for NLOS Indoor Positioning and Navigation10.1109/JIOT.2023.3245144 ↗
25. Localization Based on Parallel Robots Kinematics as an Alternative to Trilateration10.1109/TIE.2021.3050354 ↗
26. Horn, B.K.P. (2025, May 02). Celltracker. Available online: https://people.csail.mit.edu/bkph/CellTracker.
27. Geo++ (2025, May 07). Geo++ RINEX Logger. Available online: https://www.geopp.de/.
28. Jiménez Martínez, M., Quesada Olmo, N., Villar Cano, M., Paredes Asencio, J., and Marqués Mateu, A. (2025, May 07). Ajuste Gaussiano de Redes por el Método de Incrementos de Coordenadas. Valencia, Spain. Available online: http://www.racv.es/files/Ajuste_gaussiano_de_redes_metodo_incremento_coordenadas.pdf.
29. Berné Valero, J.L., Garrido Villén, N., and Capilla Roma, R. (2023). GNSS: Geodesia Espacial y Geomática, Editorial Universitat Politècnica de València.
30. Ghilani, C.D., and Wolf, P.R. (2006). Adjustment Computations: Spatial Data Analysis, John Wiley & Sons.10.1002/9780470121498 ↗
31. Strang, G., and Borre, K. (1997). Linear Algebra, Geodesy, and GPS, Wellesley-Cambridge Press.
32. Leick, A., Rapoport, L., and Tatarnikov, D. (2015). GPS Satellite Surveying, John Wiley & Sons. [4th ed.].10.1002/9781119018612 ↗
33. Xu, G., and Xu, Y. (2016). GPS: Theory, Algorithms and Applications, Springer. [3rd ed.].
34. Sanz Subirana, J., Hernandez-Pajares, M., and Juan Zornoza, J.M. (2013). GNSS Data Processing: Fundamentals and Algorithms, ESA Communications.
35. (2025, March 28). Gobierno de España; Ministerio para la Transformación Digital y de la Función Pública; Secretaría de Estado para la Sociedad de la Información y la Agenda Digital. Infoantenas. Available online: https://geoportal.minetur.gob.es/VCTEL/vcne.do.
36. Li, B., Harvey, B., and Gallagher, T. (2013, January 28–31). Using Barometers to Determine the Height for Indoor Positioning. Proceedings of the International Conference on Indoor Positioning and Indoor Navigation (IPIN), Montbéliard, France.
37. Sun, Z., Gao, W., Tao, X., Pan, S., Wu, P., and Huang, H. (2024). Semi-Tightly Coupled Robust Model for GNSS/UWB/INS Integrated Positioning in Challenging Environments. Remote Sens., 16.10.3390/rs16122108 ↗
38. Zhang, F., Li, J., Zhang, X., Duan, S., and Yang, S.-H. (2025). Indoor Fusion Positioning Based on “IMU-Ultrasonic-UWB” and Factor Graph Optimization Method. arXiv.
39. Schwarzbach, P., Michler, A., and Michler, O. (2023). Grid-Based Hybrid 3DMA GNSS and Terrestrial Positioning. arXiv.10.33012/2023.19227 ↗
40. Google Maps Platform (2025, March 26). Geolocation API Overview. Available online: https://developers.google.com/maps/documentation/geolocation/overview?hl=es-419.