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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 6

Multi-task indoor Wi-Fi fingerprinting positioning method based on LCVAE-CNN

Wu Shixun
Zeng Xinrui
Xu Kai
Lan Zhangli
Zhang Miao
Jin Yue
School of Information Science & Engineering, Chongqing Jiaotong University, Chongqing 400074, China
DOI: 10.19734/j.issn.1001-3695.2024.10.0461

Abstract

Indoor Wi-Fi received signal strength indicator (RSSI) fingerprinting widely supports location-based services. However, it faces challenges such as the difficulty of data collection and severe RSSI fluctuations caused by dynamic environmental changes, which hinder achieving high-accuracy localization. To improve localization accuracy under data scarcity and dynamic environments, this paper proposes a dual-encoder structure that independently processes RSSI data and location coordinates. The study introduces a geographic information loss function and constructs a Location Conditional Variational Autoencoder (LCVAE) model to generate fingerprint data with geographic accuracy, enhancing the localization model's performance. Additionally, the research designs a shared convolutional neural network (CNN) feature extraction layer, integrating both classification and regression functions, and presents a multitask indoor Wi-Fi fingerprint positioning method based on LCVAE-CNN. Experimental results show that the proposed LCVAE-CNN method achieves a floor classification accuracy of 98.80% and a Mean Positioning Error (MPE) of 6.79 meters on the UJIIndoorLoc dataset, and 97.22% and 5.44 meters respectively on the Tampere dataset. Compared to five existing methods, the approach improves floor classification accuracy by at least 1.9% and reduces MPE by a minimum of 19%.

Foundation Support

重庆市自然科学基金资助项目(CSTB2024NSCQ-MSX0275)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.10.0461
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 6

Publish History

[2025-03-10] Accepted Paper

Cite This Article

吴仕勋, 曾鑫睿, 徐凯, 等. 基于LCVAE-CNN的多任务室内Wi-Fi指纹定位方法 [J]. 计算机应用研究, 2025, 42 (6). (2025-03-10). https://doi.org/10.19734/j.issn.1001-3695.2024.10.0461. (Wu Shixun, Zeng Xinrui, Xu Kai, et al. Multi-task indoor Wi-Fi fingerprinting positioning method based on LCVAE-CNN [J]. Application Research of Computers, 2025, 42 (6). (2025-03-10). https://doi.org/10.19734/j.issn.1001-3695.2024.10.0461. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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