Indoor localization using transformer ensemble regression and LED signals
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Từ khóa:
Localization
ensemble learning
transformer encoder
LED
Tóm tắt
Improving the localization accuracy under the influence of multipath reflections and signal interference in indoor localization systems using visible light signals remains a complex and challenging task. In this study, we propose utilizing the transformer architecture in a localization system based on light intensity signals of 16 LEDs. By leveraging the self-attention mechanism, the model can detect and focus on the locations with the highest relevance. The predictions are aggregated thanks to an ensemble strategy. Simulation results show that the proposed method achieves a Root Mean Square Error of approximately 0.334 m for the entire room (5x5 m), 0.14 m for the central region (3×3 m), and 0.39 m for the remaining areas near the walls and corners.
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[1] N. S. Ahmad, "Recent advances in WSN-based indoor localization: A systematic review of emerging technologies, methods, challenges, and trends," IEEE Access, vol. 12, pp. 180674–180714, 2024. doi: 10.1109/ACCESS.2024.3509516.
[2] S. Wang, S. Zhang, J. Ma, and O. A. Dobre, "Graph neural network-based WiFi indoor localization system," in Proc. IEEE Global Communications Conf. (GLOBECOM), Cape Town, South Africa, 2024, pp. 116–120. doi: 10.1109/GLOBECOM52923.2024.10901150.
[3] T. Shi and W. Gong, "A survey of Bluetooth indoor localization," in Proc. 2024 IEEE 10th Conf. on Big Data Security on Cloud (BigDataSecurity), New York City, NY, USA, 2024, pp. 71–77. doi: 10.1109/BigDataSecurity62737.2024.00020.
[4] X. Zhou, L. Chen, Y. Ruan and R. Chen, "Indoor Localization With Multi-Beam of 5G New Radio Signals," IEEE Transactions on Wireless Communications, vol. 23, no. 9, pp. 11260–11275, Sept. 2024. doi: 10.1109/TWC.2024.3380737.
[5] S. A. Kharmeh, E. Natsheh, R. Nasrallah, and M. Masri, "Triangulation-enhanced WiFi-based autonomous localization and navigation system: A low-cost approach," in Proc. 2024 22nd Int. Conf. on Research and Education in Mechatronics (REM), Amman, Jordan, 2024, pp. 69–74. doi: 10.1109/REM63063.2024.10735691.
[6] K. Beigi and H. Shah-Mansouri, "An intelligent indoor positioning algorithm based on Wi-Fi and Bluetooth Low Energy," in Proc. 2024 IEEE Wireless Communications and Networking Conf. (WCNC), Dubai, United Arab Emirates, 2024, pp. 1–6. doi: 10.1109/WCNC57260.2024.10570531.
[7] Z. Yi et al., "Multimodal indoor localization using crowdsourced radio maps," in Proc. 2024 IEEE Int. Conf. on Robotics and Automation (ICRA), Yokohama, Japan, 2024, pp. 13666–13672. doi: 10.1109/ICRA57147.2024.10610683.
[8] S. Yongchareon, J. Yu, and J. Ma, "Efficient deep learning-based device-free indoor localization using passive infrared sensors," Sensors, vol. 25, no. 6, Art. no. 1362, 2025.
[9] D. Wang, M. Masannek, S. May, and A. Nüchter, "Infradar-localization: Single-chip infrared- and radar-based Monte Carlo localization," in Proc. 2023 IEEE 19th Int. Conf. on Automation Science and Engineering (CASE), Auckland, New Zealand, 2023, pp. 1–8. doi: 10.1109/CASE56687.2023.10260572.
[10] L. Danys et al., “Visible light communication and localization: A study on tracking solutions for Industry 4.0 and the Operator 4.0,” Journal of Manufacturing Systems, vol. 64, pp. 535–545, 2022. [Online]. Available: https://doi.org/10.1016/j.jmsy.2022.07.011.
[11] H. Yang et al., "An advanced integrated visible light communication and localization system," IEEE Transactions on Communications, vol. 71, no. 12, pp. 7149–7162, Dec. 2023. doi: 10.1109/TCOMM.2023.3309823.
[12] Y. Yu, B. Zhu, Z. Zhang, L. Wang, L. Wu, and J. Dang, "Indoor visible light localization algorithm with the optimal optical angle-of-arrival estimator," in Proc. 2021 2nd Information Communication Technologies Conf. (ICTC), Nanjing, China, 2021, pp. 194–198. doi: 10.1109/ICTC51749.2021.9441621.
[13] F. Wu, N. Stevens, L. De Strycker, and F. Rottenberg, "Enhancing RSS-based visible light positioning by optimal calibrating the LED tilt and gain," arXiv preprint arXiv:2404.18650, 2024. [Online]. Available: https://arxiv.org/abs/2404.18650.
[14] Y. Wang, J. Hu, H. Jia, W. Hu, M. Hassan, A. Uddin, B. Kusy, and M. Youssef, "Spectral-Loc: Indoor localization using light spectral information," Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., vol. 7, no. 1, Art. no. 37, pp. 1–26, Mar. 2023. doi: 10.1145/3580878.
[15] O. Kerdjidj et al., "Uncovering the potential of indoor localization: Role of deep and transfer learning," IEEE Access, vol. 12, pp. 73980–74010, 2024. doi: 10.1109/ACCESS.2024.3402997.
[16] I. Cappelli et al., "Enhanced visible light localization based on machine learning and optimized fingerprinting in wireless sensor networks," IEEE Transactions on Instrumentation and Measurement, vol. 72, pp. 1–10, 2023, Art. no. 9503410. doi: 10.1109/TIM.2023.3240220.
[17] X. Oh, R. Lim, S. Foong, and U.-X. Tan, "Marker-based localization system using an active PTZ camera and CNN-based ellipse detection," IEEE/ASME Transactions on Mechatronics, vol. 28, no. 4, pp. 1984–1992, Aug. 2023. doi: 10.1109/TMECH.2023.3274363.
[18] X. Cao, Y. Zhuang, X. Wang, T. Yu, J. Zhou, and J. Jiang, "Deep-learning-enhanced visible light positioning system based on the LED array," IEEE Internet of Things Journal, vol. 11, no. 12, pp. 21985–21995, Jun. 15, 2024. doi: 10.1109/JIOT.2024.3377506.
[19] Z. Ghassemlooy, W. Popoola, and S. Rajbhandari, Optical Wireless Communications: System and Channel Modeling with MATLAB. Boca Raton, FL, USA: CRC Press, 2012.
[20] A. Vaswani et al., "Attention Is All You Need," Advances in Neural Information Processing Systems (NeurIPS), vol. 30, pp. 5998–6008, 2017. doi: 10.48550/arXiv.1706.03762.
[21] Z. Zhang, R. Tian, and Z. Ding, “TrEP: Transformer-Based Evidential Prediction for Pedestrian Intention with Uncertainty,” Proceedings of the AAAI Conference on Artificial Intelligence, vol. 37, no. 3, pp. 3534–3542, 2023. doi: 10.1609/aaai.v37i3.25463.
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Feb 28, 2026
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Cách trích dẫn
Tran, H. Q., và H. Le-Quoc. “Indoor Localization Using Transformer Ensemble Regression and LED Signals”. Tạp Chí Khoa học Và Công nghệ - Đại học Đà Nẵng, vol 24, số p.h 1, Tháng Hai 2026, tr 13-18, doi:10.31130/ud-jst.2026.24(1).356E.
