Optimizing indoor localization accuracy with neural network performance metrics and software-defined IEEE 802.11az Wi-Fi set-up
Yükleniyor...
Tarih
2023-10-28
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Accurately classifying regions based on Wi-Fi signals can be a difficult task, especially when considering different frequency values. In this study, we aimed to improve the accuracy of indoor localization by developing a novel approach that does not rely on pre-trained models. To achieve this, fingerprints from the IEEE 802.11az standard were randomly selected, and the data samples were trained using parameterized station characteristics and neural network hyperparameters. The impact of each parameter on the localization accuracy was measured, and performance monitoring metrics such as F1-Measure and confusion matrix-based metrics were evaluated. Furthermore, the Thompson sampling (TS) algorithm was employed to determine the optimal parameters, which helped to achieve the best possible accuracy. The proposed approach demonstrated improved accuracy in region localization compared to conventional heuristic approaches which typically yield an accuracy range of 65% to 77%. The proposed approach achieved up to 80% accuracy in region localization and could be a promising solution for indoor localization in various settings.
Açıklama
Anahtar Kelimeler
Convolutional neural network (CNN), IEEE 802.11az Wi-Fi standard, Optimization, Thompson sampling (TS), Heuristic methods, IEEE standards, Indoor positioning systems, Wi-Fi, Wireless local area networks (WLAN), Indoor localization, Localisation, Localization accuracy, Neural-networks
Kaynak
10th International Conference on Wireless Networks and Mobile Communications (WINCOM)
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
Sayı
Künye
Kouhalvandi, L., Aygün, S., Matekovits, L. & Miramirkhani, F. (2023). Optimizing indoor localization accuracy with neural network performance metrics and software-defined IEEE 802.11az Wi-Fi set-up. Paper presented at the 10th International Conference on Wireless Networks and Mobile Communications (WINCOM), 1-4. doi:10.1109/WINCOM59760.2023.10322984
