Experimental testbed evaluation of cell level indoor localization algorithm using Wi-Fi and LoRa protocols

Abstract

Exact location of an object is not required in some scenarios of indoor localization and all we need to know is the area or a cell where the object is present in a room or a hall. For instance, the object to be located is large and we are interested in knowing the locations of the cell in which the object lies, or we want to find the quadrant of a room in which the object of interest lies. For such cases, in this paper, we propose a novel 2-phase cell localization algorithm based on trilateration. In the first phase we find the path loss exponent for each anchor node using RSSIs and in second phase we divide the available space into virtual cells and find the location of the cell in which the object is present. We have conducted real testbed experiments using Wi-Fi and LoRa with different transmission powers and calculated the error. Results show that the proposed algorithm successfully performs cell localization and Wi-Fi based localization is better than that of LoRa. Moreover, we have also studied how the accuracy of localization is affected by cell size in both of the wireless protocol.