Neural Network Handoff Decision in Mobile Cellular using Received Signal Strength and Traffic Intensity

Please use this identifier to cite or link to this item: http://www.repository.rmutt.ac.th/xmlui/handle/123456789/1317

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DC Field	Value	Language
dc.contributor.author	Pramote Anunvrapong
dc.contributor.author	Phichet Moungnoul
dc.date.accessioned	2014-02-12T02:50:43Z
dc.date.accessioned	2020-09-24T04:33:04Z	-
dc.date.available	2014-02-12T02:50:43Z
dc.date.available	2020-09-24T04:33:04Z	-
dc.date.issued	2003
dc.identifier.issn	1685-5280
dc.identifier.uri	http://www.repository.rmutt.ac.th/dspace/handle/123456789/1317	-
dc.description	Journal of Engineering, RIT Volume 3 Issue 2, January – June 2003	en_US
dc.description.abstract	This paper proposes the handoff approach by means of Neural Network for mobile telephone system, such as Global System for Mobile communication (GSM), especially focus on received signal strength (RSS) and traffic intensity (TI). A model of Base Transceiver Station (BTS) or cell, 7 cells, that have several traffic intensity. And using the principle of the mobiles in the hysteresis area can connect to more than one cell for handoff to the lower traffic intensity cell. The result shown that the proposal can reduce the drop calls, keeps the call blocking for acceptation of Grade of Service (GOS) and decreases the unnecessary handoffs)	en_US
dc.language.iso	en	en_US
dc.publisher	Rajamangala University of Technology Thanyaburi. Faculty of Engineering	en_US
dc.subject	Neural Network	en_US
dc.subject	Network	en_US
dc.title	Neural Network Handoff Decision in Mobile Cellular using Received Signal Strength and Traffic Intensity	en_US
dc.type	Article	en_US
Appears in Collections:	บทความ (Article - EN)

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Y.02 Vol.3 p.27-32 2003.pdf	Neural Network Handoff Decision in Mobile Cellular using Received Signal Strength and Traffic Intensity	1.07 MB	Adobe PDF	View/Open