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

机译:使用高阶马尔可夫模型的下一代无线网络的呼叫准入控制

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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 wireless 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.
机译:下一代无线网络(NGWN)将是异构的,它将具有一起运行的不同无线接入技术(RAT)。无线电资源管理(RRM)是NGWN的主要挑战之一。呼叫准入控制(CAC)机制是无线电资源管理技术中的一种,它在确保工作在不同应用程序上的用户具有所需的QoS方面发挥着重要作用,这些应用程序具有要由无线网络满足的QoS要求的多种性质。在这种普遍情况下要解决的关键挑战之一是在具有不同带宽需求的多个业务之间分配可用的信道容量,以保证业务的QoS要求。呼叫阻塞概率就是这样一种QoS参数。无线网络和更好的QoS,希望降低呼叫阻塞的可能性。在这种惯用方案中,创建分析性能模型非常有利。在本文中,我们提出了一种基于高阶马尔可夫链的呼叫接纳控制框架,以有效地处理NGWN中的呼叫阻塞概率,并为移动用户提供最佳QoS。在提出的算法中,我们考虑了具有不同QoS要求的三类流量。从绩效模型获得的结果令人鼓舞和乐观,表明需要CAC智能决策系统。

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