Paper Info
Title
Communication-Driven Localization and Mapping for Millimeter Wave Networks.
Abstract
Millimeter wave (mmWave) communications are an essential component of 5G-and-beyond ultra-dense Gbitls wireless networks, but also pose significant challenges related to the communication environment. Especially beam-training and tracking, device association, and fast handovers for highly directional mmWave links may potentially incur a high overhead. At the same time, such mechanisms would benefit greatly from accurate knowledge about the environment and device locations that can be provided through simultaneous localization and mapping (SLAM) algorithms. In this paper we tackle the above issues by proposing CLAM, a distributed mmWave SLAM algorithm that works with no initial information about the network deployment or the environment, and achieves low computational complexity thanks to a fundamental reformulation of the angle-differences-of-arrival mmWave anchor location estimation problem. All information required by CLAM is collected by a mmWave device thanks to beam training and tracking mechanisms inherent to mmWave networks, at no additional overhead. Our results show that CLAM achieves sub meter accuracy in the great majority of cases. These results are validated via an extensive experimental measurement campaign carried out with 60-GHz mmWave hardware.
Year
Venue
Field
2018
IEEE INFOCOM
Wireless network,Gigabit,Extremely high frequency,Computer science,Network deployment,Real-time computing,Simultaneous localization and mapping,Handover,Distributed computing,Computational complexity theory
DocType
ISSN
Citations 
Conference
0743-166X
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Joan Palacios1225.09
Guillermo Bielsa281.85
Paolo Casari3274.84
Jörg Widmer43924328.38