Research on indoor location scheme and mobility management strategy based on location information

Qiongyue Ke; Shuai Liang

doi:10.1117/12.2681699

1 June 2023 Research on indoor location scheme and mobility management strategy based on location information

Qiongyue Ke, Shuai Liang

Proceedings Volume 12718, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023); 127181F (2023) https://doi.org/10.1117/12.2681699
Event: International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023), 2023, Nanjing, China

Abstract

The services required by wireless network users are generally based on the location requirements. How to accurately locate the users in the wireless network and select the network which can provide the best service for access is the key to improve the user experience. At present, accurate positioning can be achieved in outdoor environment, but the accuracy of indoor positioning method needs to be improved. In addition, how to achieve effective switching in different networks according to users'needs during the mobile process is also a major difficulty. This paper collects user positioning information in wireless networks by studying high-precision indoor positioning algorithms and effective mobility management strategies. Thus, a fingerprint positioning model based on RSSI is built on the premise of guaranteeing good service quality for end users. RSSI of each access point in the actual location area is collected to form an offline fingerprint database. At the same time, an improved extreme learning machine algorithm location model based on particle swarm optimization is proposed to match and locate RSSI in user and fingerprint libraries. Finally, the simulation results show that the positioning scheme proposed in this paper can effectively reduce the positioning error compared with the traditional positioning algorithms.

Citation Download Citation

Qiongyue Ke and Shuai Liang "Research on indoor location scheme and mobility management strategy based on location information", Proc. SPIE 12718, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023), 127181F (1 June 2023); https://doi.org/10.1117/12.2681699

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KEYWORDS

Databases

Neural networks

Data storage

Evolutionary algorithms

Artificial neural networks

Particle swarm optimization

Matrices

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