DocumentCode
2253177
Title
A DRA scheme based on Hopfield neural networks methodology
Author
García, N. ; Pérez-Romero, J.
Author_Institution
Univ. Pompeu Fabra, Barcelona
fYear
2006
fDate
16-19 May 2006
Firstpage
583
Lastpage
586
Abstract
This paper proposes a dynamic resource allocation (DRA) algorithm that makes use of the Hopfield neural network (HNN) methodology, which provides a fast way of finding the optimum resource when formulated as a combinational problem. The proposed algorithm is applied to both the scheduling of downlink transmissions in a CDMA scenario with delay-oriented services, and real time services, although by a proper modification of the constraints imposed in the energy function, it could be easily extended to other services or access technologies. The algorithm is evaluated by means of simulations, revealing its ability to adapt to the specific service and traffic conditions. Finally, the convergence issues related to HNN methodology are considered in the light of the obtained results
Keywords
Hopfield neural nets; code division multiple access; convergence; resource allocation; telecommunication computing; telecommunication services; telecommunication traffic; CDMA scenario; DRA scheme; Hopfield neural networks methodology; combinational problem; convergence issues; delay-oriented services; downlink transmission scheduling; dynamic resource allocation algorithm; energy function; optimum resource; real time services; traffic conditions; Bit rate; Delay effects; Downlink; Electronic mail; Hopfield neural networks; Multiaccess communication; Quality of service; Real time systems; Resource management; Throughput;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrotechnical Conference, 2006. MELECON 2006. IEEE Mediterranean
Conference_Location
Malaga
Print_ISBN
1-4244-0087-2
Type
conf
DOI
10.1109/MELCON.2006.1653168
Filename
1653168
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