基于纠错码的无线传感器网络目标定位
Target Localization in Wireless Sensor Networks using Error Correcting Codes
摘要：
在这项工作中，我们考虑在无线传感器网络（WSNs）中使用量化数据的目标定位的任务。我们提出了一个能量有效的定位方案，通过建模它作为一个迭代分类问题。我们设计了基于编码的迭代目标定位方法，其中在每次迭代中，融合中心（FC）解决了M元假设检验问题，并决定下一次迭代的感兴趣区域（ROI）。即使在网络中存在拜占庭（恶意）传感器的情况下，基于编码的迭代方法也能很好地工作。我们进一步考虑了非理想信道的影响。我们建议使用软判决解码来补偿由于本地传感器和FC之间存在衰落信道而造成的损失。我们评估所提出的方案的拜占庭容错能力和目标区域的检测概率方面的性能。我们还提出了性能界限，这有助于我们在设计系统。我们提供了渐近分析所提出的计划，并表明，该计划实现完美的区域检测时，传感器的数量趋于无穷大的噪声方差无关。我们的数值结果表明，所提出的计划提供了类似的性能，在均方误差（MSE）相比，传统的极大似然估计（MLE），但计算效率更高，是弹性的错误，由于拜占庭和非理想信道。
英文摘要：
In this work, we consider the task of target localization using quantized data in Wireless Sensor Networks (WSNs). We propose an energy efficient localization scheme by modeling it as an iterative classification problem. We design coding based iterative approaches for target localization where at every iteration, the Fusion Center (FC) solves an M-ary hypothesis testing problem and decides the Region of Interest (ROI) for the next iteration. The coding based iterative approach works well even in the presence of Byzantine (malicious) sensors in the network. We further consider the effect of non-ideal channels. We suggest 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 evaluate the performance of the proposed schemes in terms of the Byzantine fault tolerance capability and probability of detection of the target region. We also present performance bounds which help us in designing the system. We provide asymptotic analysis of the proposed schemes and show that the schemes achieve perfect region detection irrespective of the noise variance when the number of sensors tends to infinity. Our numerical results show that the proposed schemes provide a similar performance in terms of Mean Square Error (MSE) as compared to the traditional Maximum Likelihood Estimation (MLE) but are computationally much more efficient and are resilient to errors due to Byzantines and non-ideal channels.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
