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Intelligent simulation for the estimation of the uplink outage probabilities in CDMA networks

机译:智能仿真,用于估算CDMA网络中的上行链路中断概率

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In CDMA mobile networks, callers that are transmitting through a power station may cause interference at other power stations. When many users are already connected in the network, a new call may cause the signal to noise ratio to drop below a tolerance threshold. This phenomenon is called 'outage' and it provides an important measure of performance, useful in the design and control of the system. Evaluating this probability analytically has proven unsuccessful and only approximations exist today. Direct simulation of such networks is at present very slow because outage occurs infrequently - it may take hours to simulate directly a realistic model if a reasonable precision is desired. Thus this approach is not useful for design problems where one wishes to evaluate and compare performance of many different network models. In this work we implement a change of measure to estimate the outage probability using importance sampling. We present a functional estimator and a stochastic approximation method that are capable of learning the best parameters for the change of measure.
机译:在CDMA移动网络中,通过某个电站发送的呼叫者可能会在其他电站上造成干扰。当网络中已经连接了许多用户时,新呼叫可能会导致信噪比下降到容限阈值以下。这种现象称为“中断”,它提供了重要的性能指标,可用于系统的设计和控制。通过分析评估这种可能性已被证明是不成功的,目前仅存在近似值。由于很少发生断电,因此目前对此类网络的直接仿真非常缓慢-如果需要合理的精度,则可能需要数小时才能直接仿真实际模型。因此,这种方法对于希望评估和比较许多不同网络模型性能的设计问题没有用。在这项工作中,我们实施了一种度量变更,以通过重要性抽样来估计中断概率。我们提出了一种功能估计器和一种随机近似方法,它们能够学习最佳的参数以改变量度。

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