University of Oulu

N. Jayaweera et al., "LiDAR aided Wireless Networks - LoS Detection and Prediction based on Static Maps," 2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall), London, United Kingdom, 2022, pp. 1-6, doi: 10.1109/VTC2022-Fall57202.2022.10012788

LiDAR aided wireless networks : LoS detection and prediction based on static maps

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Author: Jayaweera, Nalin1; Marasinghe, Dileepa1; Rajatheva, Nandana1;
Organizations: 1Centre for Wireless Communications, University of Oulu, Oulu, Finland
2Nokia Standards, Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 19.9 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2022
Publish Date: 2023-03-23


The mmWave communication up to 71 GHz is already specified in 3rd generation partnership project (3GPP)5G New Radio (NR), and communication in sub-THz bands is being studied for 6G widely in the academia and industry. Operation with very narrow beamwidths and much higher bandwidths in contrast to Frequency Range 1 (sub-6 GHz) can cater to the high data rate requirements at the expense of extra signal processing burden to overcome the unfavourable conditions such as high attenuation and scattering in the presence of obstacles. Such severe signal power attenuation caused by an obstacle may degrade the network performance due to link failures occurring as a result of line-of-sight (LoS) to non-LoS (NLoS) transitions. These limitations raise the necessity of a sensing system to collect situational awareness data to assist the wireless communication network. This work proposes a method to improve the LoS detection and user localization accuracy using multiple light detection and ranging (LiDAR) sensors co-located in access points (APs). We also propose an approach to predict the LoS transitions based on static LiDAR maps and the proposed method detected the LoS transition 400ms before its occurrence.

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Series: IEEE Vehicular Technology Conference
ISSN: 1550-2252
ISSN-E: 2577-2465
ISSN-L: 1550-2252
ISBN: 978-1-6654-5468-1
ISBN Print: 978-1-6654-5469-8
Pages: 1 - 6
Article number: 10012788
DOI: 10.1109/vtc2022-fall57202.2022.10012788
Host publication: 2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)
Conference: IEEE Vehicular Technology Conference
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
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