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A semi-Markov decision process-based joint call admission control for inter-RAT cell re-selection in next generation wireless networks

机译:基于半马尔可夫决策过程的联合呼叫允许控制,用于下一代无线网络中的RAT间小区重选

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In the next generation wireless networks (NGWNs), where different radio access technologies (RAT) will coexist and work in collaboration to provide ubiquitous access, a mechanism called Joint Call Admission Control (JCAC) will play an important role by deciding whether or not an incoming service request will be accepted according to an admission constraint as well as determining in which RAT (among the available) it will be connected. In this paper, we propose an optimal JCAC for inter-RAT cell re-selection problem also referred to as initial RAT selection in co-located wireless networks, which supports both real-time services and non-real-time services. To properly meet the JCAC goals, we propose a cost function that weigh two criteria: the blocking cost function, which takes into account the priority of each service class in each RAT, and the alternative acceptance cost, which reflects the multiplicity of RATs working in a collaborative fashion, mandatory in NGWN. We use the framework of Semi-Markov Decision Process (SMDP) to formulate the optimization problem and the value iteration algorithm to compute the optimal policy. Our model still takes into consideration the ratio between the radius of the co-located RATs and shows how it may impact on optimal initial RAT selection. Numerical results, supported by an analysis of the structure of the optimal policy, show that the proposed optimal JCAC selects for real-time service class the biggest RAT and for non-real-time service class the smallest one. This optimal JCAC policy is ratified by the current trend in the design of NGWN and also follows the 3rd Generation Partnership Project (3GPP) expectations.
机译:在下一代无线网络(NGWN)中,不同的无线电接入技术(RAT)将共存并协同工作以提供无处不在的接入,一种称为联合呼叫准入控制(JCAC)的机制将通过确定进入服务请求将根据准入约束以及确定将连接到哪个RAT(在可用的RAT中)被接受。在本文中,我们提出了一种用于RAT间小区重选问题的最优JCAC,该问题也称为共址无线网络中的初始RAT选择,它同时支持实时服务和非实时服务。为了正确地满足JCAC的目标,我们提出了一个成本函数,该函数权衡两个标准:阻塞成本函数,它考虑了每个RAT中每个服务类别的优先级;以及替代接受成本,它反映了在其中运行的RAT的多样性。在NGWN中是强制性的协作方式。我们使用半马尔可夫决策过程(SMDP)框架来制定优化问题,并使用值迭代算法来计算最优策略。我们的模型仍然考虑了共处的RAT半径之间的比率,并显示了它如何影响最佳的初始RAT选择。通过对最优策略结构的分析支持的数值结果表明,所提出的最优JCAC为实时服务等级选择最大的RAT,为非实时服务等级选择最小的RAT。 NGWN设计的当前趋势批准了这种最佳的JCAC策略,并且遵循了第三代合作伙伴计划(3GPP)的期望。

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