LiDAR aided wireless networks : LoS detection and prediction based on static maps
Jayaweera, Nalin; Marasinghe, Dileepa; Rajatheva, Nandana; Hakola, Sami; Koskela, Timo; Tervo, Oskari; Karjalainen, Juha; Tiirola, Esa; Hulkkonen, Jari (2023-01-18)
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
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https://urn.fi/URN:NBN:fi-fe2023032333038
Tiivistelmä
Abstract
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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