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Optimal call admission control for voice and data traffic in mobile communication networks

机译:移动通信网络中语音和数据流量的最佳呼叫允许控制

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摘要

In this paper, we propose a new call admission control (CAC) scheme for voice calls in mobile communication networks. Rejection of a hand-off call is more undesirable than that a new call, for a hand-off call loss couses a severer mental pain. By quantifying their respective pains, we consider them as different costs. The key point of our CAC is restricting new calls in order to minimize the total expected costs per unit time over the long time term. An optimal policy is derived from a semi-Markov decision process in which the interval between two consecutive decision epochs is exponentially distributed. Based on this potimal policy, we calculate the steady probability with respect to the number of estabished voice connections on the uplink. Thereafter, we evaluate the blocking and forced termination probabilities for voice traffic. Furthermore, we present an analytic model for the integranted voice and data traffic on the downlink. The state of this model stands for the number of voice calls in OFF state and data packets in the system at the beginning of every frame on condition that the number of voice connections is fixed. After the steady state probability for this model is calculated, we examine the effect of CAC on the throughput and waiting time of data packets at low, middle and high voice load conditions. We find that the forced termination probability is improved by our CAC scheme at the sacrifice of the blocking probability and channel utilization for voice calls. Basides our CAC is effective for data traffic at middle and high voice load condition.
机译:在本文中,我们提出了一种用于移动通信网络中语音呼叫的新呼叫准入控制(CAC)方案。与新呼叫相比,不希望转接呼叫,因为转接呼叫丢失会带来更严重的精神痛苦。通过量化它们各自的痛苦,我们认为它们是不同的成本。我们的CAC的重点是限制新呼叫,以使长期内每单位时间的总预期成本最小化。从半马尔可夫决策过程中得出最佳策略,在该过程中,两个连续决策时期之间的间隔呈指数分布。基于此最佳策略,我们计算相对于上行链路上已建立的语音连接数的稳定概率。此后,我们评估语音流量的阻塞和强制终止概率。此外,我们为下行链路上的集成语音和数据流量提供了一个解析模型。该模型的状态代表在固定语音连接数的情况下,每帧开始时处于关闭状态的语音呼叫数和系统中数据包的数量。在计算出该模型的稳态概率之后,我们研究了CAC对低,中和高语音负载条件下数据包的吞吐量和等待时间的影响。我们发现,通过牺牲语音的阻塞概率和信道利用率,通过我们的CAC方案可以提高强制终止的概率。我们的CAC可以有效应对中高语音负载情况下的数据流量。

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