Work

Fingerprint positioning of users devices in long term evolution cellular network using K nearest neighbour algorithm

Year: 2020

Type: article

Abstract: The rapid exponential growth in wireless technologies and the need for public safety has led to increasing demand for location-based services. Terrestrial cellular networks can offer acceptable position estimation for users that can meet the statutory requirements set by the Federal Communications Commission in case of network-based positioning, for safety regulations. In this study, the proposed radio frequency pattern matching (RFPM) method is implemented and tested to determine a user’s location effectively. The RFPM method has been tested and validated in two different environment. The evaluations show remarkable results especially in the Micro cell scenario, at 67% of positioning error 15m and at 90% 31.78m for Micro cell scenario, with results of 75.66m at 67% and 141.4m at 90% for Macro cell scenario.

Source: International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering

DOI: 10.11591/ijece.v11i1.pp528-535

Authors: Mohammed J. Alhasan, Sarmad Muneer Abdulhussein, Ali H. K. Khwayyir

Institution: Al-Furat Al-Awsat Technical University

Language: English

Topic: Indoor and Outdoor Localization Technologies

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W3087777205

FWCI: 0.169

Cites: 23

Cited by: 3

Related to: 10