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Byzantine tolerant target localization in wireless sensor networks over non-ideal channels

机译:在非理想通道上无线传感器网络中的拜占庭耐受目标定位

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In [1], we have proposed an energy efficient localization scheme by modeling it as an iterative classification problem. We designed coding based iterative approaches for target localization where at every iteration, the Fusion Center (FC) solves an M-ary hypothesis test and decides the Region of Interest (ROI) for the next iteration. We also considered the presence of Byzantine (malicious) sensors in the network. In this paper, we further investigate the localization scheme proposed in [1] over non-ideal channels and propose the use of soft-decision decoding to compensate for the loss due to the presence of fading channels between the local sensors and the FC. We provide the performance evaluation of the soft-decision decoding approach in terms of the mean square error of location estimate and probability of detection of the target region.
机译:在[1]中,我们通过将其作为迭代分类问题建立了节能定位方案。我们设计了基于编码的针对目标本地化的迭代方法,在每次迭代时,融合中心(FC)解决了M-ARY假设试验,并决定了下一次迭代的感兴趣区域(ROI)。我们还考虑了网络中存在拜占庭(恶意)传感器的存在。在本文中,我们进一步研究了在非理想通道上[1]中提出的定位方案,并提出了使用软判决解码来补偿由于局部传感器和Fc之间存在衰落通道的损耗。我们根据位置估计的均方误差和目标区域检测概率提供软判决解码方法的性能评估。

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