Open AccessResearch on mmWave IoV Beam Tracking Based on EKF
Author(s) -
Yu Sun,
Chenwei Feng,
Wei-Ming Lin,
Zhang Lin,
Huangbin Zeng,
Zhuo Li
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2216/1/012019
Subject(s) - computer science , the internet , tracking (education) , extremely high frequency , economic shortage , real time computing , tracking error , kalman filter , transmission (telecommunications) , telecommunications , artificial intelligence , psychology , pedagogy , linguistics , philosophy , control (management) , government (linguistics) , world wide web
The rapid development of 5G communication provides a huge opportunity for the research on the Internet of vehicles. With the increasing shortage of low-frequency spectrum resources and the demand for high transmission rates for the architecture of the internet of vehicles, the highly qualified millimeter wave has been combined into the research on the internet of vehicles. However, due to the various characteristics of millimeter wave and the limitation of the complex communication environment of the internet of vehicles, how to achieve stable beam tracking is a big problem that needs to be solved urgently. This paper mainly introduces an extended Kalman filter algorithm with updated threshold to solve the problem of continuous stable beam tracking of millimeter waveInternet of vehicles. Simulation shows that this method has lower tracking error than the original algorithm, and better overcomes the problem of continuous accumulation of tracking error of the original algorithm.