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Journal Article A Ray Tracing and Joint Spectrum Based Clustering and Tracking Algorithm for Internet of Intelligent Vehicles
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Authors
Luoyan Zhu, Danping He, Bo Ai, Ke Guan, Shuping Dang, Junhyeong Kim, Heesang Chung, Zhangdui Zhong
Issue Date
2020-09
Citation
Journal of Communications and Information Networks, v.5 no.3, pp.265-281
ISSN
2096-1081
Publisher
Post & Telecom Press
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.23919/JCIN.2020.9200890
Project Code
20HH3100, [Social issue] QoE improvement of open Wi-Fi on public transportation for the reduction of communication expense, Chung Hee Sang
Abstract
Driven by the rapid growth in information services provided by the Internet and the appearance of new multimedia applications, millimeter wave is foreseen as a key enabler towards the Internet of intelligent vehicles (IoIV) for urban traffic safety enhancement. In this regard, cluster-based channel modeling has become an important research topic in the realm of emergency communications. To fully understand the cluster-based channel model, a series of vehicle-to-infrastructure (V2I) channel simulations at 22.6 GHz are conducted by a three-dimensional ray tracing (RT) simulator. The clustering and tracking algorithm is proposed and analyzed from three aspects by the obtained simulation results. The multiple signal classification estimation spectrum is applied to restrain the influence of antenna sidelobes and identify targets at first. Based on the fundamentals, the clusters can be identified and subsequently tracked using the proposed approach. The impacts of antenna sidelobes, angle resolution of beam rotation, and non-line-of-sight propagation path on the performance of clustering and tracking are evaluated. The multi-component-level RT results are adopted as comparison benchmarks, which reflect the ground truth. This work aims to provide a full picture of the clustering characteristics for designing and analyzing emergency communication systems.
KSP Keywords
2.6 GHz, Angle resolution, Antenna sidelobes, Channel modeling, Communication system, Emergency Communications, Information services, Line-Of-Sight(LOS), Multi-component, Multiple Signal Classification, Non Line-of-sight(NLOS)