Positioning a Mobile Subscriber in a Cellular Network System based on Signal Strength



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INTRODUCTION

In positioning a mobile subscriber (Location
Tracking), a mobile user is provided with
information pertaining to its current position. It
is one of the popular areas of wireless
computing research. Researchers paid attention
to Positioning Systems after the Federal
Communications Commission (FCC), mandated
that all wireless carriers in the United States
must provide a certain degree of accuracy in
pinpointing location of mobile users who dial
911. The regulation was passed in 1996 and still
most wireless carriers haven’t implemented
such a system [2]. The main reason behind this
is the cost associated with the implementation of
such a system. According to an estimate, a
precise GSM based position system incurs a
high cost (approx. U.S. $ 10,000) per base
station.



RELATED WORK

So far the research includes facility location
algorithms, which involve locating large scale
wireless networks (WiMAX) and use of
approximated radio maps algorithms [3]. A GPS
receiver provides location estimation based on
the time of arrival of four or more L-band
signals from a network of 24 satellites.
Commercial GPS receivers costing $150,
accurately determine position within
approximately 50 meters. The size and cost of
GPS receivers will improve as the number of
commercial GPS units increases [4]. Wireless
service providers appear unwilling to adopt GPS
as the principal location technology within the
handset or car phone.


TRIANGULAING A MOBILE USER

Triangulating a mobile device involves three
steps. The first step is to retrieve the signal
strength values from the related BTS. The
second step involves approximating the
distances from the corresponding BTS with the
help of the received signal strength.


CONCLUSION
We have presented an approach to approximate
the location or position of a mobile user based
upon signal strength of a mobile device by using
different values of ‘k’. In addition we have
shown that this approach provides better results
in terms of accuracy as compared to signature
database approach, which requires that the
covered area be continuously monitored and the
signature database be continuously updated.