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Pattern classification based handoff using fuzzy logic and neural nets

机译:基于模糊逻辑和神经网络的基于模式分类的切换

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Conventional handoff algorithms are susceptible to varying propagation environments, traffic intensities, and user speeds due to the lack of parameter adaptation. This paper proposes a new class of adaptive handoff algorithms that views the handoff problem as a pattern classification problem. Adaptive direction biasing is proposed to reduce the processing load and improve the cell membership properties. The paper shows that the desired balance among the system characteristics can be achieved by making appropriate design tradeoffs in a pattern classification based handoff framework.
机译:由于缺乏参数适应,传统的切换算法易于不同的传播环境,交通强度和用户速度。 本文提出了一类新的自适应切换算法,将切换问题视为模式分类问题。 提出了自适应方向偏置以减少处理负荷并改善单元隶属性。 该文件表明,通过在基于模式分类的切换框架中进行适当的设计权衡,可以实现系统特征之间所需的平衡。

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