Record Details

DYNAMIC LOCATION AREA PLANNING IN CELLULAR NETWORK BY VIRTUALLY PERSONALIZE LOCATION AREA MANAGEMENT

Shodhganga@INFLIBNET

View Archive Info
 
 
Field Value
 
Title DYNAMIC LOCATION AREA PLANNING IN CELLULAR NETWORK BY VIRTUALLY PERSONALIZE LOCATION AREA MANAGEMENT
—
 
Contributor Dr. Dhaval R. Kathiriya
 
Subject Dynamic Location Area, Mobility Prediction, Super Vector Regression, Location Updata, Paging
 
Description Location management is an essential function in cellular networks that allows the network to maintain the position of subscribers, in terms of location areas. In GSM, the whole network divided into different LAs, which are very useful to find current location as well as mobility pattern of the mobile users. There are various methods, adopted by cellular companies like static and dynamic, to plan better LA in cellular network. LA planning is very important because location management cost, Location Update and Paging Cost, is derived based on that. The work presented in this research concentrates on Dynamic LA planning and Mobility Prediction methods for mobile users. The work carried out focuses on better LA planning for minimum radio bandwidth utilization as well as mobility prediction for providing better services to mobile users. Using this research work Location Management cost will be reduced, better resource allocation and good QoS, without call dropping and blocking, can be provided to the mobile users. This research work is divided into three parts: in first part, MUs types (Predefine Estimated and Random users) are found out based on user s movement in the cellular network. In second part, dynamic location area (DLA) is created for the users which are regularly visiting some cells in cellular network. These frequently visited cells are assigned to MUs as an individual LA. Finally in third part, mobility prediction of MU is found out based on the mobility pattern in cellular network which help the network in resource reservation. For creating DLA and finding mobility prediction accuracy in cellular network three methods, viz Apriori, HMM and proposed SVR, implemented and results are compared with static method. Amongst these methods, proposed SVR reduce more signaling cost (location management cost) and give better mobility prediction accuracy which is also compared with static method.
newline
newline
References p.73-76, Publications p. 77
 
Date 2018-10-16T05:18:25Z
2018-10-16T05:18:25Z
Oct-11
October-18
—
 
Type Ph.D.
 
Identifier http://hdl.handle.net/10603/218611
 
Language English
 
Relation 46
 
Rights university
 
Format xxi, p. 1-77
—
DVD
 
Coverage Mobile Networking
 
Publisher Ahmedabad
Gujarat Technological University
Computer/IT Engineering
 
Source University