Connected Objects Geo-Localization Based on SS-RSRP of 5G Networks

The Global Positioning System (GPS) is not the only way to solve connected objects’ geo-localization problems; it is also possible to use the mobile network infrastructure to geo-locate objects connected to the network, using antennas and signals designed for voice and data transfer, such as the 5th...

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Autores principales:	Ahmed Bannour, Ahmed Harbaoui, Fawaz Alsolami
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	reference signal received power micro-cell geo-localization SS-RSRP 5G Electronics TK7800-8360
Acceso en línea:	https://doaj.org/article/d004563d7a7c43b79e7ac355f9e8eba5
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spelling	oai:doaj.org-article:d004563d7a7c43b79e7ac355f9e8eba52021-11-25T17:24:20ZConnected Objects Geo-Localization Based on SS-RSRP of 5G Networks10.3390/electronics102227502079-9292https://doaj.org/article/d004563d7a7c43b79e7ac355f9e8eba52021-11-01T00:00:00Zhttps://www.mdpi.com/2079-9292/10/22/2750https://doaj.org/toc/2079-9292The Global Positioning System (GPS) is not the only way to solve connected objects’ geo-localization problems; it is also possible to use the mobile network infrastructure to geo-locate objects connected to the network, using antennas and signals designed for voice and data transfer, such as the 5th generation network. 5G is considered as a least expensive solution because there is no specific equipment to set up. As long as the object is in an area covered by the network, it connects to the nearest 5G Micro-Cell (MC). Through exchange of signals with the MC node we can locate the object. Currently, this location is very fast with less than 5 s but not very precise because it depends on the number of MC antennas of the operator in question and their distance. This paper presents a novel technique to geo-locate connected object in a covered 5G area. We exploit the 5G SS-RSRP used for signal quality measurement, to estimate the distance between two Connected Objects (COs) in move and in a dense urban area. The overall goal is to present a new concept laying on the 5G SS-RSRP signalling. The proposed solution takes into consideration the Deterministic and the Stochastic effect of the received signals which is not treated by the previous works. The accuracy is optimum even after approaching to the distance of one meter which is not reached in previous works too. Our method can also be deployed in the upcoming 5G network since it relies on 5G signals itself. This work and that of Wang are both based on RSRP and give comparable theoretical complexities therefore comparable theoretical execution times as well. However, to obtain a reliable learning Wang requires a huge amount of data which makes it difficult to get a real time aspect of this algorithm. The use of RSRP and the elimination of the learning phase will give more chance to our work to achieve desired performances. Numerical results show the appropriateness of the proposed algorithms and good location accuracy of around one meter. The Cramer Rao Lower Bound derivations shows the robustness of the proposed estimator and consolidate the work.Ahmed BannourAhmed HarbaouiFawaz AlsolamiMDPI AGarticlereference signalreceived powermicro-cellgeo-localizationSS-RSRP5GElectronicsTK7800-8360ENElectronics, Vol 10, Iss 2750, p 2750 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	reference signal received power micro-cell geo-localization SS-RSRP 5G Electronics TK7800-8360
spellingShingle	reference signal received power micro-cell geo-localization SS-RSRP 5G Electronics TK7800-8360 Ahmed Bannour Ahmed Harbaoui Fawaz Alsolami Connected Objects Geo-Localization Based on SS-RSRP of 5G Networks
description	The Global Positioning System (GPS) is not the only way to solve connected objects’ geo-localization problems; it is also possible to use the mobile network infrastructure to geo-locate objects connected to the network, using antennas and signals designed for voice and data transfer, such as the 5th generation network. 5G is considered as a least expensive solution because there is no specific equipment to set up. As long as the object is in an area covered by the network, it connects to the nearest 5G Micro-Cell (MC). Through exchange of signals with the MC node we can locate the object. Currently, this location is very fast with less than 5 s but not very precise because it depends on the number of MC antennas of the operator in question and their distance. This paper presents a novel technique to geo-locate connected object in a covered 5G area. We exploit the 5G SS-RSRP used for signal quality measurement, to estimate the distance between two Connected Objects (COs) in move and in a dense urban area. The overall goal is to present a new concept laying on the 5G SS-RSRP signalling. The proposed solution takes into consideration the Deterministic and the Stochastic effect of the received signals which is not treated by the previous works. The accuracy is optimum even after approaching to the distance of one meter which is not reached in previous works too. Our method can also be deployed in the upcoming 5G network since it relies on 5G signals itself. This work and that of Wang are both based on RSRP and give comparable theoretical complexities therefore comparable theoretical execution times as well. However, to obtain a reliable learning Wang requires a huge amount of data which makes it difficult to get a real time aspect of this algorithm. The use of RSRP and the elimination of the learning phase will give more chance to our work to achieve desired performances. Numerical results show the appropriateness of the proposed algorithms and good location accuracy of around one meter. The Cramer Rao Lower Bound derivations shows the robustness of the proposed estimator and consolidate the work.
format	article
author	Ahmed Bannour Ahmed Harbaoui Fawaz Alsolami
author_facet	Ahmed Bannour Ahmed Harbaoui Fawaz Alsolami
author_sort	Ahmed Bannour
title	Connected Objects Geo-Localization Based on SS-RSRP of 5G Networks
title_short	Connected Objects Geo-Localization Based on SS-RSRP of 5G Networks
title_full	Connected Objects Geo-Localization Based on SS-RSRP of 5G Networks
title_fullStr	Connected Objects Geo-Localization Based on SS-RSRP of 5G Networks
title_full_unstemmed	Connected Objects Geo-Localization Based on SS-RSRP of 5G Networks
title_sort	connected objects geo-localization based on ss-rsrp of 5g networks
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/d004563d7a7c43b79e7ac355f9e8eba5
work_keys_str_mv	AT ahmedbannour connectedobjectsgeolocalizationbasedonssrsrpof5gnetworks AT ahmedharbaoui connectedobjectsgeolocalizationbasedonssrsrpof5gnetworks AT fawazalsolami connectedobjectsgeolocalizationbasedonssrsrpof5gnetworks
_version_	1718412438621126656

Connected Objects Geo-Localization Based on SS-RSRP of 5G Networks

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