An enhanced path loss model for accurate indoor distance estimation

Other Title(s)

تعزيز مسار نموذج الخسارة بتقدير دقيق للمسافة الداخلية

Dissertant

al-Shamayilah, Waid Amjad

Thesis advisor

al-Nabhan, Muhammad Musa Muhammad

Comitee Members

al-Kasasibah, Muhammad Sharari Zamil
al-Abadilah, Ahmad Muhammad
al-Harfushi, Usamah Kasab
Hammad, Mustafa Muhammad

University

Mutah University

Faculty

Information Technology College

Department

Computer Science Department

University Country

Jordan

Degree

Master

Degree Date

2016

English Abstract

Indoor localization based on received signal strength has become very popular in recent years.

Wi-Fi radio signals are highly used to navigate and locate users in indoor environments.

This is due to high availability of Wi-Fi technology within most buildings including; universities, hospitals, homes and companies.

In addition, availability of smartphones and laptops equipped with Wi-Fi adapters has increased Wi-Fi popularity.

This work presents a new approach required to enhance distance estimation process using log-distance path loss model based on Wi-Fi RSS.

The proposed approach relies on analyzing Path Loss Exponent (PLE) and Received Signal Strength (RSS) variables through a set of procedures allowing the optimal approximation of these variables.

In addition, the proposed approach provides a best-fit relationship between these variables improving estimated distance accuracy within both in Line of Sight (LOS) and Non-Line of Sight (NLOS) cases.

The proposed approach consists of three main functional steps.

The first step is responsible for measuring RSS values in different environmental settings.

The second step includes approximating optimal PLE values and its relation to RSS and estimated distance accuracy.

The outcomes of the second step are used to obtain optimal ranges of PLE values required for both LOS and NOLS environments.

Obtaining these optimal values allows to remove errors and noise in RSS and reduces the effect of signal multi-path, allowing for enhanced distance estimation in the last step.

The proposed approach was experimentally tested and evaluated using a novel evaluation methodology representing all possible navigation environments.

Several experimental scenarios were conducted measuring up-to-date and real-time signal strength measurements for mobile user in LOS and NLOS environments.

Measurements were applied to the functional approach procedures following passive analysis and statistical methods to approximate new Path Loss Model (PLM) parameters.

In addition, a comparison analysis study was carried between the proposed approach and conventional path loss models with reference to achieved distance accuracy.

Results have confirmed the advancement of distance accuracy and position performance using the proposed approach in both LOS and NLOS environments.

At a 95% confidence level, the significant difference between real distance and estimated distance was reduced using the proposed approach comparing to conventional models.

Main Subjects

Information Technology and Computer Science

No. of Pages

55

Table of Contents

• APA
• MLA
• AMA

Language

English

Data Type

Arab Theses

Record ID

BIM-731649