Hopfield neural-network-based dynamic resource allocation scheme for non-real-time traffic in wireless networks

Dynamic resource allocation (DRA) plays a fundamental role in current and future wireless networks, including 3G systems. In this paper, a scheduling DRA scheme for non-real-time (NRT) packet services in wireless system is proposed based on the use of Hopfield neural networks (HNN). The scheme exploits the fast response time of HNN for solving NP optimization problems and has been particularized for the downlink transmission in a UMTS system, although it could be easily extended to any other radio access technology. The new DRA scheme follows a delay-centric approach, since it maximizes the overall system resource utilization while minimizing the packet delay. Simulation results confirm that the proposed HNN-based DRA scheme is effective in supporting different types of NRT services, while achieving efficient utilization of radio resources. Copyright © 2008 John Wiley & Sons, Ltd.

[1]  M. Schwartz,et al.  Reservation strategies for multi-media traffic in a wireless environment , 1995, 1995 IEEE 45th Vehicular Technology Conference. Countdown to the Wireless Twenty-First Century.

[2]  M. Gudmundson.  Correlation Model for Shadow Fading in Mobile Radio Systems , 1991 .

[3]  Xavier Lagrange,et al.  Performance evaluation of a dynamic resource allocation algorithm for UMTS-TDD systems , 2000, VTC2000-Spring. 2000 IEEE 51st Vehicular Technology Conference Proceedings (Cat. No.00CH37026).

[4]  Demessie Girma,et al.  A Hopfield neural-network-based dynamic channel allocation with handoff channel reservation control , 2000, IEEE Trans. Veh. Technol..

[5]  Oscar. Lazaro de Barrio.  Dynamic radio resource management algorithms and traffic models for emerging mobile communication systems , 2002 .

[6]  J. Monserrat,et al.  Hopfield Neural Network Algorithm for Dynamic Resource Allocation in WCDMA Systems , 2006, 2006 3rd International Symposium on Wireless Communication Systems.

[7]  Oriol Sallent,et al.  A downlink admission control algorithm for UTRA-FDD , 2002, 4th International Workshop on Mobile and Wireless Communications Network.

[8]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[9]  David Gomez-Barquero,et al.  User bandwidth usage-driven HNN neuron excitation method for maximum resource utilization within packet-switched communication networks , 2006, IEEE Communications Letters.

[10]  M. Forti,et al.  A condition for global convergence of a class of symmetric neural circuits , 1992 .

[11]  I. Forkel,et al.  Dynamic channel allocation in UMTS terrestrial radio access TDD systems , 2001, IEEE VTS 53rd Vehicular Technology Conference, Spring 2001. Proceedings (Cat. No.01CH37202).

[12]  Chang Wook Ahn,et al.  QoS provisioning dynamic connection-admission control for multimedia wireless networks using a Hopfield neural network , 2004, IEEE Transactions on Vehicular Technology.

[13]  Kai-Yeung Siu,et al.  Dynamic assignment of orthogonal variable-spreading-factor codes in W-CDMA , 2000, IEEE Journal on Selected Areas in Communications.

[14]  J. Perez-Romero,et al.  Packet scheduling algorithms for interactive and streaming services under QoS guarantee in a CDMA system , 2002, Proceedings IEEE 56th Vehicular Technology Conference.

[15]  J J Hopfield,et al.  Neurons with graded response have collective computational properties like those of two-state neurons. , 1984, Proceedings of the National Academy of Sciences of the United States of America.

[16]  Yan Wang,et al.  Optimal Admission Control for Multi-Class of Wireless Adaptive Multimedia Services , 2001 .

[17]  Symeon Papavassiliou,et al.  Integration of mobile agents and genetic algorithms for efficient dynamic network resource allocation , 2001, Proceedings. Sixth IEEE Symposium on Computers and Communications.

[18]  Hussein M. Abdel-Wahab,et al.  A Rate-Based Borrowing Scheme for QoS Provisioning in Multimedia Wireless Networks , 2002, IEEE Trans. Parallel Distributed Syst..

[19]  Ibrahim W. Habib,et al.  Adaptive allocation of resources and call admission control for wireless ATM using genetic algorithms , 2000, IEEE Journal on Selected Areas in Communications.

[20]  Marimuthu Palaniswami,et al.  Neural techniques for combinatorial optimization with applications , 1998, IEEE Trans. Neural Networks.