5G NR indoor localization with smartphones

Xiaoxuan Tao; Liang Chen

doi:10.1117/12.2640925

2 December 2022 5G NR indoor localization with smartphones

Xiaoxuan Tao, Liang Chen

Proceedings Volume 12288, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022); 1228818 (2022) https://doi.org/10.1117/12.2640925
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022), 2022, Zhuhai, China

Abstract

With the development of commercial 5G, the demands for indoor positioning with 5G signals are also increasing gradually. In this paper, we explore the commercial 5G signals for indoor positioning. Based on 5G smartphones available in the shelf, an Android application is developed to collect 5G New Radio (NR) signals and the fingerprinting methods of K-nearest neighbor (KNN) and Convolution Neural Network (CNN) have been investigated. The localization performance of 5G NR signals is tested in an office building. In the static experiments, the average positioning accuracy achieved by these two methods are 2.39m and 3.22m, respectively, while in the dynamic indoor tests, the average positioning accuracy is 3.53m and 3.08m. In both experiments, CNN performs better than KNN. The implementation shows that indoor localization by commercial 5G signals using existing 5G smartphones can meet the requirements of indoor office scenarios.

Citation Download Citation

Xiaoxuan Tao and Liang Chen "5G NR indoor localization with smartphones", Proc. SPIE 12288, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022), 1228818 (2 December 2022); https://doi.org/10.1117/12.2640925

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