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Power allocation for power-limited sensor networks with application in object classification

机译:具有在对象分类中的电源限制传感器网络的功率分配

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This publication analyzes the power allocation problem for a distributed wireless sensor network which is based on ultra-wide bandwidth communication technology. The network has power-limited sensor nodes and it is used to classify target objects. In the considered scenarios, the absence, the presence, or the type of an object is observed by the sensors independently. Since the observations are transmitted over noisy communication channels, and are thus unreliable, the disturbed observations are fused into a reliable global decision in order to increase the overall classification probability. In [1] an information theoretic approach, that aims at maximization of the mutual information, has been employed. It enables the analytical allocation of the given total power to the sensor nodes so as to optimize the overall classification probability. We follow the same idea and improve on the results in [1] by a smart selection of the sensor nodes. Furthermore, we investigate the power constraint per sensor node and extend the results hereby.
机译:本出版物分析了基于超宽带宽通信技术的分布式无线传感器网络的功率分配问题。网络具有有限的传感器节点,它用于对目标对象进行分类。在所考虑的场景中,传感器独立地观察到对象的缺失,存在或类型。由于观察结果通过嘈杂的通信信道传输,因此不可靠地,所干扰的观察被融合成可靠的全局决定,以便增加整体分类概率。在[1]中,旨在最大化相互信息的信息理论方法。它使得给定总功率的分析分配给传感器节点,以优化整体分类概率。我们通过传感器节点的智能选择,遵循相同的想法和改进[1]中的结果。此外,我们调查每个传感器节点的功率约束,并在此扩展结果。

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