Call Admission Control for Next Generation Wireless Networks Using Higher Order Markov Model

Ramesh Babu H.S, Gowrishankar Gowrishankar, Satyanarayana P.S
<span title="2010-01-19">2010</span> <i title="Canadian Center of Science and Education"> <a target="_blank" rel="noopener" href="" style="color: black;">Computer and Information Science</a> </i> &nbsp;
The Next generation wireless networks (NGWN) will be heterogeneous which will have different radio access technologies (RATs) operating together. The Radio Resource Management (RRM) is one of the key challenges in NGWN. The Call admission control (CAC) mechanism is one of the Radio Resource Management technique plays instrumental role in ensuring the desired QoS to the users working on different applications which are having the diversified nature of QoS requirements to be fulfilled by the
more &raquo; ... ess networks. One of the key challenges to be addressed in this prevailing scenario is the distribution of the available channel capacity amongst the multiple traffic with different bandwidth requirements so as to guarantee the QoS requirements of the traffic .The call blocking probability is one such QoS parameter for the wireless network and for better QoS it is desirable to reduce the call blocking probability. In this customary scenario it is highly advantageous to bring about an analytic Performance model. In this paper we propose a call admission control framework based on higher order Markov chains to effectively handle the call blocking probability in NGWN and to provide optimal QoS for the mobile users. In the proposed algorithm we have considered three classes of traffic having different QoS requirements. The results obtained from the Performance model are encouraging and optimistic and indicates the need of an intelligent decision making system for CAC.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="">doi:10.5539/cis.v3n1p192</a> <a target="_blank" rel="external noopener" href="">fatcat:uljrenjf4zbklkeq6gdnwixr3e</a> </span>
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