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A Markov Model for Performance Evaluation of CRRM Algorithms in a Co-Located GERAN/UTRAN/WLAN Scenario

机译:在共同定位的GERAN / UTRAN / WLAN场景中用于CRRM算法性能评估的马尔可夫模型

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摘要

Next generation wireless networks will be heterogeneous. Multiple Radio Access Technologies (RATs) will be colocated in the same area. A challenge arising is the efficient radio resource management among overlapped RATs. The concept of Common Radio Resource Management (CRRM) has been proposed in the literature. One of the key issues of CRRM is the RAT selection algorithm. In order to support the conceptual development of Radio Access Technology (RAT) selection algorithms in heterogeneous networks, the theory of Markov model is used. This paper proposes a three-dimensional Markov model for an integrated GERAN/UTRAN/WLAN network based on the extension of existing two co-located RATs Markov models. The performance of two basic RAT selection algorithms: load balancing (LB) based and service based algorithms are evaluated in terms of call blocking probability. The numerical results obtained from our Markov model are validated by simulation results.
机译:下一代无线网络将是异构的。多个无线电接入技术(RAT)将位于同一区域。出现的挑战是重叠RAT之间的有效无线资源管理。文献中已经提出了公共无线电资源管理(CRRM)的概念。 CRRM的关键问题之一是RAT选择算法。为了支持异构网络中无线接入技术(RAT)选择算法的概念发展,使用了马尔可夫模型的理论。本文基于现有的两个同位RAT马尔可夫模型的扩展,提出了用于集成GERAN / UTRAN / WLAN网络的三维马尔可夫模型。根据呼叫阻塞概率评估两种基本RAT选择算法的性能:基于负载平衡(LB)和基于服务的算法。仿真结果验证了从我们的马尔可夫模型获得的数值结果。

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