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Game Theory for Networks. 11th International EAI Conference, GameNets 2022, Virtual Event, July 7–8, 2022, Proceedings

Research Article

MU-PDR: A Method of Fingerprint Passive Positioning for WiFi6 Based on MU-RTS/CTS

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-23141-4_3,
        author={Ningchi Zhang and Cheng Zhong and Qinghai Ou and Pengcheng Lu and La Bao and Yan Liu and Sujie Shao},
        title={MU-PDR: A Method of Fingerprint Passive Positioning for WiFi6 Based on MU-RTS/CTS},
        proceedings={Game Theory for Networks. 11th International EAI Conference, GameNets 2022, Virtual Event, July 7--8, 2022, Proceedings},
        proceedings_a={GAMENETS},
        year={2023},
        month={1},
        keywords={Fingerprint positioning Passive positioning WiFi6},
        doi={10.1007/978-3-031-23141-4_3}
    }
    
  • Ningchi Zhang
    Cheng Zhong
    Qinghai Ou
    Pengcheng Lu
    La Bao
    Yan Liu
    Sujie Shao
    Year: 2023
    MU-PDR: A Method of Fingerprint Passive Positioning for WiFi6 Based on MU-RTS/CTS
    GAMENETS
    Springer
    DOI: 10.1007/978-3-031-23141-4_3
Ningchi Zhang1, Cheng Zhong2, Qinghai Ou1, Pengcheng Lu2, La Bao3, Yan Liu4, Sujie Shao4,*
  • 1: Beijing Fibrlink Communications Co., Ltd.
  • 2: Xiong’an New District Power Supply Company of State Grid Hebei Electric Power Co., Ltd., Xiong’an
  • 3: State Grid Information and Communication Industry Group Co., Ltd.
  • 4: State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications
*Contact email: buptssj@bupt.edu.cn

Abstract

With the rapid development of wireless communication technology and mobile Internet, requirements for accuracy and efficiency of location services are on the increase. In recent years, WiFi fingerprint passive positioning technology has received more and more attention from the academic community. RSS fingerprint is usually adopted in this field, but it has some inherent defects in real-time positioning due to its unstable acquisition timing. Packet Delivery Rate (PDR) fingerprint has been proposed in recent years, which has great advantages over RSS fingerprint in passive positioning scenario. However, it still has the problems of low positioning efficiency and huge resource consumption. Therefore, this paper proposes an improved positioning method named MU-PDR (Multi User Packet Delivery Rate), which utilizes the newly introduced MU-RTS/CTS feature in WiFi6. The corresponding MU-PDR fingerprint acquisition and positioning methods are proposed to optimize the performance of PDR-like fingerprint in multi-target scenes. Finally, simulation result shows that MU-PDR has higher efficiency than traditional PDR in multi-target scenario, which is illustrated by the significant reduction of channel resource occupation under the same accuracy requirements.

Keywords
Fingerprint positioning Passive positioning WiFi6
Published
2023-01-08
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-23141-4_3
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