@inproceedings{0ad7a9bb06fe46cb8645e4836481ef5d,
title = "Beamforming-Based Location Management Under an O-RAN Architecture Using Spark Streaming",
abstract = "A streaming-based Indoor Positioning System (IPS) is developed for beam-based cellular networks that apply directional beam patterns for communications and sensing. The proposed IPS is designed to provide a real-time positioning service by leveraging the computing framework and the streaming modules of Apache Spark streaming. Under the Spark Streaming framework, a beam and model-based location tracking method is designed and optimized for positioning precision and resource utilization. Experiments show that the average positioning error of the proposed user tracking method is about 0.4 meters, which achieves 56.2% improvements over static locating methods. More importantly, a static timing analysis is carried out to evaluate the throughput and bottlenecks of the proposed IPS system. Based on the analysis, our proposed architecture is capable and promising for low-latency IPS provisioning under the O-RAN framework.",
keywords = "Edge Computing, O-RAN, Particle Filter, Streaming Computing, User Tracking",
author = "Ko, {Chun Hsien} and Wu, {Sau Hsuan} and Chen, {Yu An} and Tang, {Chih Hsuan}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE Global Communications Conference, GLOBECOM 2023 ; Conference date: 04-12-2023 Through 08-12-2023",
year = "2023",
doi = "10.1109/GLOBECOM54140.2023.10436859",
language = "English",
series = "Proceedings - IEEE Global Communications Conference, GLOBECOM",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "7085--7090",
booktitle = "GLOBECOM 2023 - 2023 IEEE Global Communications Conference",
address = "United States",
}