Machine Learning and Intelligent Communications. First International Conference, MLICOM 2016, Shanghai, China, August 27-28, 2016, Revised Selected Papers

Research Article

Indoor WLAN Deployment Optimization Based on Error Bound of Neighbor Matching

Download
224 downloads
  • @INPROCEEDINGS{10.1007/978-3-319-52730-7_33,
        author={Feng Qiu and Mu Zhou and Zengshan Tian and Yunxia Tang and Qiao Zhang},
        title={Indoor WLAN Deployment Optimization Based on Error Bound of Neighbor Matching},
        proceedings={Machine Learning and Intelligent Communications. First International Conference, MLICOM 2016, Shanghai, China, August 27-28, 2016, Revised Selected Papers},
        proceedings_a={MLICOM},
        year={2017},
        month={2},
        keywords={WLAN Network optimization Location fingerprinting Neighbor matching Error bound},
        doi={10.1007/978-3-319-52730-7_33}
    }
    
  • Feng Qiu
    Mu Zhou
    Zengshan Tian
    Yunxia Tang
    Qiao Zhang
    Year: 2017
    Indoor WLAN Deployment Optimization Based on Error Bound of Neighbor Matching
    MLICOM
    Springer
    DOI: 10.1007/978-3-319-52730-7_33
Feng Qiu1,*, Mu Zhou1,*, Zengshan Tian1,*, Yunxia Tang1,*, Qiao Zhang1,*
  • 1: Chongqing University of Posts and Telecommunications
*Contact email: qiufeng245@outlook.com, zhoumu@cqupt.edu.cn, tianzs@cqupt.edu.cn, 13629735505@139.com, 18716322725@139.com

Abstract

In this paper, we propose a novel indoor Wireless Local Area Network (WLAN) deployment optimization approach based on the error bounds of Neighbor Matching Algorithms (NMAs). We derive out the closed-form solution to the localization errors of NMAs with respect to the environmental size, interval of Reference Points (RPs), number of neighbors, and locations of Access Points (APs). Based on the requirement of localization precision, as well as networking overhead, we optimize the networking parameters, like the interval of RPs, number of neighbors, and locations of APs. Finally, the extensive experiments are conducted to demonstrate that the proposed approach can effectively improve the localization precision of NMAs in indoor WLAN environment.