IOT-5G USER TRACKING IN A 5G NETWORK USING 60 GHZ MM-WAVES BASED ON AN ABF-ED ALGORITHMS FOR A CLUTTERED INDOOR ENVIRONMENT

This paper presents a user tracking algorithm in an IoT-5G Network (or IoT-5GN). Hereby, we aim at studying and evaluating the sensing performances of the IoT-5G Access Point (or IoT-5G AP) primary signal by the IoT-5G user in a cluttered indoor environment using an energy detector (or ED) algorithm...

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Bibliographic Details
Published in:International archives of the photogrammetry, remote sensing and spatial information sciences. remote sensing and spatial information sciences., 2021-12, Vol.XLVI-4/W5-2021, p.7-13
Main Authors: Adardour, H. E., Kameche, S., Irid, S. M. H., Benmostefa, O., Benamar, A. A.
Format: Article
Language:English
Subjects:
5G mobile communication
Algorithms
Error analysis
Error detection
Evaluation
Indoor environments
Millimeter waves
Probability theory
Tracking
Wireless networks
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Summary:This paper presents a user tracking algorithm in an IoT-5G Network (or IoT-5GN). Hereby, we aim at studying and evaluating the sensing performances of the IoT-5G Access Point (or IoT-5G AP) primary signal by the IoT-5G user in a cluttered indoor environment using an energy detector (or ED) algorithm and an Alpha-&-Beta Filter (ABF or α-β-F) estimator. The 5G primary signal (or 5G-PS) frequency that we would like to detect is: 60 GHz. As a result, the 5G-PS sensing via the proposed ABF-ED algorithm, enabled us to track the IoT-5G user inside of the IoT-5G AP coverage area. The performances of the proposed ABF-ED algorithm in this paper work is evaluated by the probability of total detection error (or PTDE) measure. Through different scenarios simulations, the performances and robustness of the proffered algorithm are demonstrated.
ISSN:2194-9034
1682-1750
2194-9034
DOI:10.5194/isprs-archives-XLVI-4-W5-2021-7-2021