A learning approach for call admission control under QoS constraints in cellular networks

Xu Yang, John Bigham

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

Abstract

A new approach for learning Call Admission Control (CAC) schemes that can provide Quality of Service (QoS) guarantees to ongoing calls from several classes of traffic with different resource requirements is presented. Comparison with two other CAC schemes shows that the new approach is not only capable of utilizing the network resource to maximize revenue but also maintain the handover dropping rate (CDR) under a prescribed upper bound while still maintaining an acceptable Call Blocking Rate (CBR). The learning CAC scheme is shown to work successfully in the presence of smoothly changing arrival rates of traffic. The CAC policy is obtained through a form of NeuroEvolution (NE) algorithm.

Original languageEnglish
Title of host publication2006 IEEE Singapore International Conference on Communication Systems, ICCS 2006
PublisherIEEE Computer Society
ISBN (Print)1424404118, 9781424404117
DOIs
Publication statusPublished - 2006
Event10th IEEE Singapore International Conference on Communications Systems, ICCS 2006 - Singapore, Singapore
Duration: 30 Oct 20061 Nov 2006

Publication series

Name2006 IEEE Singapore International Conference on Communication Systems, ICCS 2006

Conference

Conference10th IEEE Singapore International Conference on Communications Systems, ICCS 2006
Country/TerritorySingapore
CitySingapore
Period30/10/061/11/06

Keywords

  • Call admission control
  • NeuroEvlution of augmenting topologies
  • QoS constraints

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