Abstract
Nowadays, wireless communication techniques, such as WiFi, Bluetooth low energy (BLE), etc., have been pervasive in our daily lives, and not only provide convenient data transmission services, but also enable popular indoor positioning and navigation services. The placement of wireless infrastructures like WiFi access points (APs) and BLE beacons have significant influences on the performance of localization. More importantly, since APs and beacons are probably used for both network access and localization, it is necessary to take into account both coverage and localization when deploying APs and beacons. In addition, there still exist other critical challenges, including optimizing AP and beacon placement in WiFi and BLE hybrid localization and optimizing the placement of extra APs and/or beacons in an existing wireless network, which are essentially NP-complete. This paper tackles these problems of optimizing AP and beacon placement by proposing a heuristic differential evolution algorithm based on the widely used Cramer-Rao lower bound (CRLB). To be specific, the CRLB is leveraged as a metric for localization and meanwhile a coverage degree criterion is defined as a metric for coverage, both of which are incorporated into the evaluation function of the differential evolution algorithm. Furthermore, instead of using the ideal log distance path loss (LDPL) model, the more practical Motley-Keenan model is adopted to reflect the influences of obstacles that are widespread in indoor environments. On these grounds, a software is designed and implemented based on Geotools to optimize AP and beacon placement in an interactive GUI manner. Finally, extensive simulations and field experiments are conducted, and a thorough comparison confirms the efficiency and effectiveness of the proposed algorithm.
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