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Caterina Giovannetti

dblp:359/6130 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0005-9789-4614ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Wireless sensing and localization · 36% Cellular and mobile networks · 29% Vehicular, aerial and satellite networks · 18%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cellular and mobile networks › 5G NR
5G NR-V2X
0.812024
V2X Sidelink Localization of Connected Automated Vehicles · IEEE J. Sel. Areas Commun. 2024
Wireless sensing and localization
localization accuracy
0.812024
V2X Sidelink Localization of Connected Automated Vehicles · IEEE J. Sel. Areas Commun. 2024
Physical-layer communications › channel modeling
near-field propagation
0.812024
V2X Sidelink Localization of Connected Automated Vehicles · IEEE J. Sel. Areas Commun. 2024
Wireless sensing and localization
vehicle localization
0.812024
V2X Sidelink Localization of Connected Automated Vehicles · IEEE J. Sel. Areas Commun. 2024
Vehicular, aerial and satellite networks › vehicular networks
vehicle-to-everything
0.812024
V2X Sidelink Localization of Connected Automated Vehicles · IEEE J. Sel. Areas Commun. 2024
Cellular and mobile networks
5G NR
0.212024
V2X Sidelink Localization of Connected Automated Vehicles · IEEE J. Sel. Areas Commun. 2024
Cellular and mobile networks › low-latency communication
ultra-reliable low-latency communication
0.212024
V2X Sidelink Localization of Connected Automated Vehicles · IEEE J. Sel. Areas Commun. 2024

Methods — techniques the papers use, named apart from their topics

near-field propagation · 0.8antenna array · 0.8
YearPublicationVenuePosition
2024 V2X Sidelink Localization of Connected Automated Vehicles
abstract
Future automated driving relies on two pillars, (i) ultra-low-latency and reliable communications, and (ii) accurate positioning information. In particular, the knowledge of vehicle positions is becoming fundamental with the increase of the automation level, allowing autonomous navigation of the environment. Today’s positioning techniques cannot provide the accuracy, robustness, and latency required for stringent applications, like platooning, where vehicles are expected to travel at extremely short distances. In this paper, we leverage vehicle-to-everything (V2X) sidelink communication for localization purposes, capitalizing on the near-field propagation attributes of signals generated utilizing high carrier frequencies and/or large antenna arrays. Consequently, a receiving vehicle can accurately determine the transmitting vehicle’s location through V2X sidelink packet reception, obviating the need for supplementary reference nodes or stringent synchronization. Fundamental limits on localization accuracy are derived to characterize the positioning performance in vehicular contexts. A case study based on 5G new radio (NR) V2X sidelink shows how this technique is extremely promising and capable of providing high accuracy, low latency, high update rate, and high availability of position information in realistic vehicular scenarios.
Nicolò Decarli, Anna Guerra, Caterina Giovannetti, Francesco Guidi, Barbara M. Masini
IEEE J. Sel. Areas Commun.3