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Joint mobility tracking and handoff in cellular networks via sequential Monte Carlo filtering

机译:通过顺序蒙特卡洛滤波在蜂窝网络中进行联合移动性跟踪和切换

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We consider the application of sequential Monte Carlo (SMC) methodology to the problem of joint mobility tracking and handoff detection in cellular wireless communication networks. Both mobility tracking and handoff detection are based on the measurements of pilot signal strengths from certain base stations. The dynamics of the system under consideration are described by a nonlinear state-space model. Mobility tracking involves an online estimation of the location and velocity of the mobile, whereas handoff detection involves an online prediction of the pilot signal strength at some future time instants. The optimal solutions to both problems are prohibitively complex due to the nonlinear nature of the system. The SMC methods are therefore employed to track the probabilistic dynamics of the system and to make the corresponding estimates and predictions. Both hard handoff and soft handoff are considered and three novel locally optimal (LO) handoff schemes are developed based on different criteria. It is seen that under the SMC framework, optimal mobility tracking and handoff detection can be implemented naturally in a joint fashion, and significant improvement is achieved over existing methods, in terms of both the tracking accuracy and the trade-off between service quality and resource utilization during handoff.
机译:我们考虑将顺序蒙特卡洛(SMC)方法应用于蜂窝无线通信网络中的联合移动性跟踪和切换检测问题。移动性跟踪和越区切换检测均基于来自某些基站的导频信号强度的测量。所考虑系统的动力学由非线性状态空间模型描述。移动性跟踪涉及在线估计移动台的位置和速度,而越区切换检测涉及在线预测将来某个时刻的导频信号强度。由于系统的非线性特性,对这两个问题的最佳解决方案都非常复杂。因此,采用SMC方法来跟踪系统的概率动力学并做出相应的估计和预测。同时考虑了硬切换和软切换,并根据不同的标准开发了三种新颖的局部最优(LO)切换方案。可以看出,在SMC框架下,可以自然地以联合方式自然地实现最佳的移动性跟踪和越区切换检测,并且在跟踪精度和服务质量与资源之间的权衡方面都比现有方法有了明显的提高。切换期间的利用率。

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