Effective Quantised CSI-Fingerprint for DL-Based Indoor Localisation

IF 1.5 Q3 TELECOMMUNICATIONS

IET Wireless Sensor Systems Pub Date : 2025-04-08 DOI:10.1049/wss2.70003

Seiha Homma, Yuta Ida, Yasuaki Ohira, Sho Kuroda, Takahiro Matsumoto

引用次数: 0

Abstract

In recent years, indoor localisation based on channel state information (CSI) fingerprint has been actively researched because of the rapid growth of the Internet of Things (IoT). In addition, various deep learning (DL) methods such as deep neural networks (DNN) and convolutional neural networks (CNN) have been widely discussed for the indoor localisation. The CSI-fingerprint can be produced by continuous and quantised values. For the CSI-fingerprint using quantised values, good performance is achieved. However, since quantised data for the optimal level has not been sufficiently discussed, the best performance of quantisation is not indicated. Therefore, in this paper, we propose an effective quantised CSI-fingerprint for DL-based indoor localisation.

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基于dl的室内定位的有效量化csi指纹

近年来，随着物联网（IoT）的快速发展，基于信道状态信息（CSI）指纹的室内定位技术得到了积极的研究。此外，深度神经网络（DNN）和卷积神经网络（CNN）等各种深度学习（DL）方法也被广泛用于室内定位。CSI 指纹可以通过连续值和量化值生成。使用量化值生成的 CSI 指纹性能良好。然而，由于量化数据的最佳水平尚未得到充分讨论，量化的最佳性能也未得到说明。因此，本文提出了一种有效的量化 CSI 指纹，用于基于 DL 的室内定位。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IET Wireless Sensor Systems TELECOMMUNICATIONS-

CiteScore

4.90

自引率

5.30%

发文量

审稿时长

33 weeks

期刊介绍： IET Wireless Sensor Systems is aimed at the growing field of wireless sensor networks and distributed systems, which has been expanding rapidly in recent years and is evolving into a multi-billion dollar industry. The Journal has been launched to give a platform to researchers and academics in the field and is intended to cover the research, engineering, technological developments, innovative deployment of distributed sensor and actuator systems. Topics covered include, but are not limited to theoretical developments of: Innovative Architectures for Smart Sensors;Nano Sensors and Actuators Unstructured Networking; Cooperative and Clustering Distributed Sensors; Data Fusion for Distributed Sensors; Distributed Intelligence in Distributed Sensors; Energy Harvesting for and Lifetime of Smart Sensors and Actuators; Cross-Layer Design and Layer Optimisation in Distributed Sensors; Security, Trust and Dependability of Distributed Sensors. The Journal also covers; Innovative Services and Applications for: Monitoring: Health, Traffic, Weather and Toxins; Surveillance: Target Tracking and Localization; Observation: Global Resources and Geological Activities (Earth, Forest, Mines, Underwater); Industrial Applications of Distributed Sensors in Green and Agile Manufacturing; Sensor and RFID Applications of the Internet-of-Things ("IoT"); Smart Metering; Machine-to-Machine Communications.