A Learning Approach for Call Admission Control under QoS Constraints in Cellular Networks

Author

Yang, Xu ; Bigham, John

Author_Institution

QMUL Inf. Syst. Res. Centre, Macao Polytech. Inst.

fYear

2006

fDate

Oct. 2006

Firstpage

1

Lastpage

5

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

Keywords

cellular radio; quality of service; resource allocation; telecommunication congestion control; telecommunication traffic; CAC; CBR; CDR; QoS; call admission control scheme; call blocking rate; cellular network; classes of traffic; handover dropping rate; learning approach; network resource utilization; neuroevolution algorithm; quality of service guarantee; Artificial neural networks; Bandwidth; Call admission control; Communication system traffic control; Land mobile radio cellular systems; Learning; Network topology; Quality of service; Telecommunication traffic; Upper bound; Call Admission Control; NeuroEvlution of Augmenting Topologies; QoS constraints;

fLanguage

English

Publisher

ieee

Conference_Titel

Communication systems, 2006. ICCS 2006. 10th IEEE Singapore International Conference on

Conference_Location

Singapore

Print_ISBN

1-4244-0411-8

Electronic_ISBN

1-4244-0411-8

Type

conf

DOI

10.1109/ICCS.2006.301401

Filename

4085696