12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China

Research Article

AP Deployment Optimization Based on Bluetooth Fingerprint Database Discrimination

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  • @INPROCEEDINGS{10.4108/eai.29-6-2019.2282130,
        author={Haoliang  Ren and Zengshan  Tian and Mu  Zhou and Xiaoxiao  Jin and Shuai  Lu},
        title={AP Deployment Optimization  Based on Bluetooth Fingerprint Database Discrimination},
        proceedings={12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China},
        publisher={EAI},
        proceedings_a={MOBIMEDIA},
        year={2019},
        month={6},
        keywords={indoor positioning fingerprint database access point deployment greedy algorithm signal propagation model},
        doi={10.4108/eai.29-6-2019.2282130}
    }
    
  • Haoliang Ren
    Zengshan Tian
    Mu Zhou
    Xiaoxiao Jin
    Shuai Lu
    Year: 2019
    AP Deployment Optimization Based on Bluetooth Fingerprint Database Discrimination
    MOBIMEDIA
    EAI
    DOI: 10.4108/eai.29-6-2019.2282130
Haoliang Ren1,*, Zengshan Tian1, Mu Zhou1, Xiaoxiao Jin1, Shuai Lu1
  • 1: Chongqing University of Posts and Telecommunications
*Contact email: rhaoliang@qq.com

Abstract

In indoor fingerprint positioning system, Access Point (AP) deployment costs a lot of manpower and time, and the deployment efficiency of existing methods is extremely low due to the complexity and dynamics of indoor environment. In order to solve this problem, this paper proposes an optimal AP deployment algorithm. First of all, wireless signal propagation model is established from indoor environment. Then simulated fingerprint database is constructed based on initial AP deployment. Finally, greedy algorithm is selected to optimize the deployment of APs. The experimental results show that this method can be well adapted to the indoor environment with higher accuracy compared to the empirical AP deployment.