A Ray Tracing and Joint Spectrum Based Clustering and Tracking Algorithm for Internet of Intelligent Vehicles

被引:0
|
作者
Zhu L. [1 ,2 ]
He D. [1 ,2 ]
Ai B. [1 ,2 ]
Guan K. [1 ,2 ]
Dang S. [3 ]
Kim J. [4 ]
Chung H. [4 ]
Zhong Z. [1 ,2 ]
机构
[1] State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing
[2] Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications, Beijing
[3] CEMSE Division, King Abdullah University of Science and Technology (KAUST), Thuwal
[4] Moving Wireless Network Research Section, Electronics and Telecommunications Research Institute (ETRI), Daejeon
关键词
channel modeling; clustering and tracking algorithm; Internet of intelligent vehicles (IoIV); millimeter-wave; ray tracing; vehicle-to-infrastructure (V2I) communications;
D O I
10.23919/JCIN.2020.9200890
中图分类号
学科分类号
摘要
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. © 2020, Posts and Telecom Press Co Ltd. All rights reserved.
引用
收藏
页码:265 / 281
页数:16
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