DocumentCode
650326
Title
An NN-based access network selection algorithm for heterogeneous networks
Author
Hongzhi Xing ; Dawei Mu ; Xianlei Ge ; Rong Chai
Author_Institution
Key Lab. of Mobile Commun. Technol., Chongqing Univ. of Posts & Telecommun., Chongqing, China
fYear
2013
fDate
16-18 May 2013
Firstpage
378
Lastpage
383
Abstract
Next generation wireless network is expected to integrate multiple wireless technologies and provide mobile users with communication connectivity of different QoS requirements. However, the heterogeneity of access networks and the variety of user application requirements pose new challenges on access network selection scheme, i.e., selecting the optimal network for multi-interface mobile terminal (MT) in the case that multiple networks are available. In this paper, the theory of neural network (NN) is applied in designing network selection scheme for heterogeneous networks and an NN-based access network selection algorithm is proposed, which models the network characteristics based on network and user sample data and then evaluates the performance of candidate networks based on current network and service features, the candidate network with the best service performance is then chosen as the destination network Simulation results demonstrate that the proposed algorithm offers better QoS performance comparing to the traditional algorithm.
Keywords
neural nets; next generation networks; quality of service; NN-based access network selection algorithm; QoS requirements; access network selection scheme; communication connectivity; heterogeneous networks; mobile users; multiinterface mobile terminal; multiple wireless technologies; neural network; next generation wireless network; optimal network; back propagation; heterogeneous network; network modeling; network selection; neural network;
fLanguage
English
Publisher
ieee
Conference_Titel
Wireless and Optical Communication Conference (WOCC), 2013 22nd
Conference_Location
Chongqing
Print_ISBN
978-1-4673-5697-8
Type
conf
DOI
10.1109/WOCC.2013.6676396
Filename
6676396
Link To Document