The Wide Range of Regression Analysis in Distance Estimation System of the Fingerprint-Based Outdoor Wireless Access Point Localization System - ., Sutiyo; Hidayat, Risanuri; Wayan Mustika, I.; ., Sunarno (International Journal of Engineering and Technology, 2018)
The development of utilization of outdoor wireless access point devices has progressed very rapidly. Mitigation and control of the use of the frequency spectrum are very important to do so that the use of the frequency spectrum can run in accordance with government regulations. This cannot be separated from the technique of localizing the use of wireless devices. There are various localization techniques with various methods and levels of accuracy but generally, these techniques are applied indoors. Localization techniques are generally used to find the location of wireless users, not to search for access point localization. In this paper the distance estimation system from the fingerprint-based outdoor wireless access point localization system is discussed, and wireless devices working in 2.4 GHz. The distance estimation system uses regression method, and this paper aims to prove that 3rd order regression polynomial is the right regression model used for the fingerprint-based wireless access point localization. Previously this technique was applied at a distance of 0-100 meters, so this paper confirms this technique is applied at a distance of 0-1000 meters. The fingerprint is carried out in the range of 0 to 1000 meters and is divided into eleven measurement points. DataPoint consists of received signal strength (RSSfnd) and the distance of the finder to an access point that is being targeted (Dfnd). DataPoint from the fingerprinting process is analyzed by regression method and based on the results of the trendline and R2 shows that in the range of 0-1000 meters the regression method that is right to use for distance estimation system is the 3rd order polynomial regression.Â Â