Paper Info
Title
Bayesian Inference for Localization in Cellular Networks
Abstract
In this paper, we present a general technique based on Bayesian inference to locate mobiles in cellular networks. We study the problem of localizing users in a cellular network for calls with information regarding only one base station and hence triangulation or trilateration cannot be performed. In our call data records, this happens more than 50% of time. We show how to localize mobiles based on our knowledge of the network layout and how to incorporate additional information such as round-trip-time and signal to noise and interference ratio (SINR) measurements. We study important parameters used in this Bayesian method through mining call data records and matching GPS records and obtain their distribution or typical values. We validate our localization technique in a commercial network with a few thousand emergency calls. The results show that the Bayesian method can reduce the localization error by 20% compared to a blind approach and the accuracy of localization can be further improved by refining the a priori user distribution in the Bayesian technique.
Year
DOI
Venue
2010
10.1109/INFCOM.2010.5462018
INFOCOM
Keywords
DocType
ISSN
commercial network,localization error,trilateration,network layout,radiofrequency interference,cellular radio,bayesian technique,triangulation,bayesian method,bayes methods,bayesian inference,inference,gps records,localization technique,cellular network,a priori user distribution,additional information,cellular networks,general technique,base station,interference,signal to noise ratio,global positioning system,base stations,round trip time,bayesian methods
Conference
0743-166X
ISBN
Citations 
PageRank 
978-1-4244-5836-3
24
3.78
References 
Authors
11
3
Name
Order
Citations
PageRank
Hui Zang1105277.25
Francois Baccelli281286.80
Jean Bolot320310.69