Cross-Technology Localization : Leveraging Commodity WiFi to Localize Non-WiFi Device

Dian ZHANG*, Rujun ZHANG, Haizhou GUO, Peng XIANG, Xiaonan GUO

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review


Radio Frequency (RF)-based indoor localization technologies play significant roles in various Internet of Things (IoT) services (e.g., location-based service). Most such technologies require that all the devices comply with a specified technology (e.g., WiFi, ZigBee, and Bluetooth). However, this requirement limits its application scenarios in today's IoT context where multiple devices complied with different standards coexist in a shared environment. To bridge the gap, in this paper, we propose a cross-technology localization approach, which is able to localize target nodes using a different type of devices. Specifically, the proposed framework reuses the existing WiFi infrastructure without introducing additional cost to localize Non-WiFi device (i.e., ZigBee). The key idea is to leverage the interference between devices that share the same operating frequency (e.g., 2.4GHz). Such interference exhibits unique patterns that depend on the target device's location, thus it can be leveraged for cross-technology localization. The proposed framework uses Principal Components Analysis (PCA) to extract salient features of the received WiFi signals, and leverages Dynamic Time Warping (DTW), Gradient Boosting Regression Tree (GBRT) to improve the robustness of our system. We conduct experiments in real scenario and investigate the impact of different factors. Experimental results show that the average localization accuracy of our prototype can reach 1.54m, which demonstrates a promising direction of building cross-technology technologies to fulfill the needs of modern IoT context.

Original languageEnglish
Pages (from-to)3950-3969
Number of pages20
JournalKSII Transactions on Internet and Information Systems
Issue number11
Publication statusPublished - 30 Nov 2021

Bibliographical note

Funding Information:
This research is supported in part by NSFC 61872247, Shenzhen Peacock Talent Grant 827-000175, Guangdong Prenational Project 2014GKXM054, Guangdong Natural Science Foundation 2016A030313036, 2017 Guangdong Undergraduate Teaching Quality and Teaching Reform Project 839-0000026812.

Publisher Copyright:
© 2021 KSII.


  • Channel state information
  • Cross-technology
  • Indoor localization


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