基于结构干扰的无线传感器网络快速细粒度计数和识别

Dingming Wu, Chao Dong, Shaojie Tang, Haipeng Dai, Guihai Chen
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引用次数: 13

摘要

计数和识别相邻活动节点是无线传感器网络的两个基本操作。在本文中,我们提出了基于功率的计数(Poc)和基于功率的识别(Poid)两种机制,通过允许邻居同时响应轮询器来实现快速准确的计数和识别。激发我们设计的一个关键观察是,在相振干扰(CI)条件下,叠加信号的功率随着分量信号数量的增加而增加。然而,由于相位偏移和各种硬件限制(例如,ADC饱和),随着分量信号数量的增加,增加的叠加功率表现出动态和递减的回报。相位偏移的不确定性和叠加功率的收益递减特性对Poc和Poid的设计都提出了严峻的挑战。为了克服这些挑战,我们设计了延迟补偿方法来减少每个分量信号的相位偏移,并提出了一种新的与CI合作的概率估计技术。我们在1个USRP节点和50个TelosB节点的测试平台上实现了Poc和Poid,实验结果表明,Poc的准确率在97.9%以上,Poid的准确率在96.5%以上。除了高精度之外,我们的方法在大大降低能耗和估计延迟方面比最先进的解决方案具有显著的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast and fine-grained counting and identification via constructive interference in WSNs
Counting and identifying neighboring active nodes are two fundamental operations in wireless sensor networks (WSNs). In this paper, we propose two mechanisms, Power based Counting (Poc) and Power based Identification (Poid), which achieve fast and accurate counting and identification by allowing neighbors to respond simultaneously to a poller. A key observation that motivates our design is that the power of a superposed signal increases with the number of component signals under the condition of constructive interference (CI). However, due to the phase offsets and various hardware limitations (e.g., ADC saturation), the increased superposed power exhibits dynamic and diminishing returns as the number of component signals increases. This uncertainty of phase offsets and diminishing returns property of the superposed power pose serious challenges to the design of both Poc and Poid. To overcome these challenges, we design delay compensation methods to reduce the phase offset of each component signal, and propose a novel probabilistic estimation technique in cooperation with CI. We implement Poc and Poid on a testbed of 1 USRP and 50 TelosB nodes, the experimental results show that the accuracy of Poc is above 97.9%, and the accuracy of Poid is above 96.5% for most cases. In addition to their high accuracy, our methods demonstrate significant advantages over the state-of-the-art solutions in terms of substantially lower energy consumption and estimation delay.
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