Abstract:
Wireless Sensor Networks (WSN) is getting interest for its remarkable application in
different sectors like in defense for target tracking, monitoring environmental and animal
activities, medical treatment etc. In WSN nodes collect data from deployed area and then
send it to the center node for further processing. So localization is an important issue in
sensor network to locate the position from where the data is receiving to central node.
Distance to sensors estimated through several techniques. Among those techniques,
Received Signal Strength Indicator (RSSI) method is simple, inexpensive, required no
extra hardware like Global Positioning System (GPS).
In RSSI technique, the distance between nodes is determined using RSSI value. So path
loss model is necessary to establish a relation between RSSI and distance. However radio
wave propagation can be affected by different factors like floor, wall, ground, external
interference due to WLAN, human body, temperature etc. in the real environment. To get
the exact RSSI vs distance curve the accurate propagation model considering different
factors exists in the real environment is needed.
In this project work, different factors which have the effect on radio wave propagation
both in indoor and outdoor environment has been tested experimentally. The experimental
data is compared with the theoretical model data and it is observed that the basic
propagation model does not cover all the factors. So a new factor is added to the basic path
- loss model to compensate the losses due to different factors exist in real environment in
where sensors are deployed. After addition of new factor which consider the other
attenuation factors in real environment with the basic propagation model it is shown that
the proposed propagation model yields the result near to the practical data.
Description:
This thesis is submitted to the Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Electrical and Electronic Engineering, November 2010.
Cataloged from PDF Version of Thesis.
Includes bibliographical references (pages 58-60).