Received Signal Strength Based Indoor Positioning Using Bluetooth Low Energy
|Date||02. March 2018|
|Title||Received Signal Strength Based Indoor Positioning Using Bluetooth Low Energy|
|Abstract||The idea behind the Internet of Things (IoT) is to connect every object to the Internet. According to Gartner, the number of IoT devices will reach up to 20.4 billion by 2020. However, the large number of connections is only feasible with the help of wireless technologies. Bluetooth Low Energy (BLE) is a widely-used wireless technology in the IoT domain. The Physical layer (PHY) of this standard has been redesigned resulting in two types of channels. Namely: Advertisement (ADV) and data channels. ADV channels are responsible for devices discovery, connection initiation and information broadcast. Data channels are used only to exchange information during connections. In 2013, Apple introduces iBeacon which operates on these ADV channels. Beacon broadcast enabled new areas of applications such as product advertisement, medical monitoring, and indoor positioning. Among these mentioned applications, indoor positioning is the one receiving aconsiderable attention. BLE based indoor positioning relies on Received Signal Strength (RSS) technique for point-to-point distance estimation. This technique requires a path loss model to estimate the distance based on the received power. The Log-Normal Distance Model (L-NDM) is a general path loss model for every environment. However, this model has been improved to consider the multipath fading effects in indoor environments, and the result is the Log-Normal Shadowing Model (L-NSM). Yet, the later lacks generalization for every environment and frequency. There exist a considerable research of path loss characterization on Wi-Fi and ZigBee but to the best of our knowledge, an extensive study on BLE ADV channels is missed.
This thesis addresses this research gap through conducting experiments in various conditions such as different indoor and outdoor environments, different transmit power settings, background noise and antenna orientation. Path loss models based on the results of this research can be directly used for range estimation and simulation tools for modeling BLE ADV channels. The obtained results show the complexity of indoor environments and their considerable impact on RSS due to multipath fading and interference with other presented devices. The comparison of outdoor and indoor results highlights this claim.