Call admission control combined with resource allocation in 3G wireless networks

Xu Yang, John Bigham, Laurie Cuthbert

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper propose a novel learning approach that applies NeuroEvolution of Augmenting Topology (NEAT) based learning algorithm to resolve Call Admission Control (CAC) combined with resource allocation in adaptive multimedia wireless networks; this not only decides whether to accept or reject a request call, but also determines the allocated bandwidth to that requesting call. The objective is to maximize the network revenue and maintain predefined QoS constraints. The QoS constraints are classified as two categories: long period constraints and instantaneous constraints. Long period constraints are handled by a constraint handling method called Superiority of Feasible Points. Instantaneous constraints and system limitations are handled by an External Supervisor.

Original languageEnglish
Title of host publicationProceedings of 2009 IEEE International Conference on Communications Technology and Applications, IEEE ICCTA2009
Pages167-172
Number of pages6
DOIs
Publication statusPublished - 2009
Event2009 IEEE International Conference on Communications Technology and Applications, IEEE ICCTA2009 - Beijing, China
Duration: 16 Oct 200918 Oct 2009

Publication series

NameProceedings of 2009 IEEE International Conference on Communications Technology and Applications, IEEE ICCTA2009

Conference

Conference2009 IEEE International Conference on Communications Technology and Applications, IEEE ICCTA2009
Country/TerritoryChina
CityBeijing
Period16/10/0918/10/09

Keywords

  • CAC
  • Constraint optimization problem
  • NEAT
  • Resource allocation

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