非随机缺失数据:无线网络中目标干扰的表征

A. M. Chandran
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引用次数: 0

摘要

通信系统在运行过程中包括数据收集和估计。在接收端,由于信道条件、恶意攻击、接收端故障等各种原因,数据可能会丢失。其中一些情况是随机发生的,但有时,它们的出现不是随机的。这些情况可能是由于干扰的精确放置阻碍了设备之间的通信。文献中提出了不同的机制来解决这种数据丢失,通过请求重传、传播信号等。另一种方法是使用统计分析来挖掘接收到的数据,以估计非随机丢失的数据点。在统计研究中,当一个或多个调查对象由于社会、经济和健康原因跳过对一个或多个数据字段的回答时,在数据收集过程中出现非随机遗漏的数据。这些缺失的回答是通过从其他受试者收集的回答来填补的。同样,在无线网络中,受到攻击的特定节点的数据丢失可以认为是数据丢失,而不是随机丢失,可以从周围节点收集的数据中进行估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Missing Data Not At Random: Characterization of Targeted Interference in Wireless Networks
Communication systems include data collection and estimation during their operations. At the receiver, the data can be missed due to various reasons such as channel conditions, malicious attack, failure at the receiver. Some of these conditions occur at random, but sometimes, their occurrences are not random. These occurrences can be due to the precise placement of interference to impede communication between the devices. There are different mechanisms proposed in the literature to address this data loss, by requesting retransmission, spreading the signal, etc. A different approach is by using statistical analysis to mine data received to estimate the data points that are missed not at random. In the statistical study, data that are missed not at random manifest during data collection when one or more subjects involved in the survey skip their responses for one or more data fields due to social, economic, and health reasons. These missed responses are filled by imputation from the responses collected from other subjects. Similarly, in a wireless network, data lost from a particular node that is under attack can be considered as data missed not at random and can be estimated from the data collected from the surrounding nodes.
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