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Flow-level performance and capacity of wireless networks with user mobility

机译:具有用户移动性的无线网络的流量级性能和容量

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The performance evaluation of wireless networks is severely complicated by the specific features of radio communication, such as highly variable channel conditions, interference issues, and possible hand-offs among base stations. The latter elements have no natural counterparts in wireline scenarios, and create a need for novel performance models that account for the impact of these characteristics on the service rates of users.rnMotivated by the above issues, we review several models for characterizing the capacity and evaluating the flow-level performance of wireless networks carrying elastic data transfers. We first examine the flow-level performance and stability of a wide family of so-called μ-fair channel-aware scheduling strategies. We establish that these disciplines provide maximum stability, and describe how the special case of the Proportional Fair policy gives rise to a Processor-Sharing model with a state-dependent service rate. Next we turn attention to a network of several base stations with inter-cell interference. We derive both necessary and sufficient stability conditions and construct lower and upper bounds for the flow-level performance measures. Lastly we investigate the impact of user mobility that occurs on a slow timescale and causes possible hand-offs of active sessions. We show that the mobility tends to increase the capacity region, both in the case of globally optimal scheduling and localrnα-fair scheduling. It is additionally demonstrated that the capacity and user throughput improve with lower values of the fairness index α.
机译:无线网络的性能评估由于无线电通信的特定特征而变得极为复杂,例如信道条件高度可变,干扰问题以及基站之间可能的切换。在有线方案中,后一种元素没有天然的对应物,因此需要一种新颖的性能模型,以说明这些特征对用户服务费率的影响。出于上述问题的考虑,我们回顾了几种表征容量和评估的模型。进行弹性数据传输的无线网络的流量级性能。我们首先检查了一系列广泛的所谓μ-公平通道感知调度策略的流量级性能和稳定性。我们确定这些规则可提供最大的稳定性,并描述比例公平政策的特殊情况如何导致处理器共享模型具有依赖于状态的服务速率。接下来,我们将注意力转向具有小区间干扰的几个基站的网络。我们导出必要和充分的稳定性条件,并为流量水平性能指标构建上下限。最后,我们调查了在缓慢的时间范围内发生的用户移动性的影响,这些影响会导致活动会话的移交。我们表明,在全局最优调度和局部公平调度的情况下,移动性都倾向于增加容量区域。另外证明,公平指数α的值越低,容量和用户吞吐量越提高。

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