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Neighbor discovery in a wireless sensor network: Multipacket reception capability and physical-layer signal processing

机译:无线传感器网络中的邻居发现:多数据包接收功能和物理层信号处理

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摘要

In randomly deployed networks, such as sensor networks, an important problem for each node is to discover its neighbor nodes so that the connectivity amongst nodes can be established. In this paper, we consider this problem by incorporating the physical layer parameters in contrast to the most of the previous work which assumed a collision channel. Specifically, the pilot signals that nodes transmit are successfully decoded if the strength of the received signal relative to the interference is sufficiently high. Thus, each node must extract signal parameter information from the superposition of an unknown number of received signals. This problem falls naturally in the purview of random set theory (RST) which generalizes standard probability theory by assigning sets, rather than values, to random outcomes. The contributions in the paper are twofold: First, we introduce the realistic effect of physical layer considerations in the evaluation of the performance of logical discovery algorithms; such an introduction is necessary for the accurate assessment of how an algorithm performs. Secondly, given the double uncertainty of the environment (that is, the lack of knowledge of the number of neighbors along with the lack of knowledge of the individual signal parameters), we adopt the viewpoint of RST and demonstrate its advantage relative to classical matched filter detection method.
机译:在诸如传感器网络之类的随机部署的网络中,每个节点的一个重要问题是发现其邻居节点,以便可以在节点之间建立连接。在本文中,我们通过结合物理层参数来考虑此问题,这与先前大多数假设碰撞通道的工作形成对比。具体地,如果接收信号相对于干扰的强度足够高,则节点发送的导频信号被成功解码。因此,每个节点必须从未知数量的接收信号的叠加中提取信号参数信息。这个问题自然属于随机集理论(RST)的范畴,该理论通过将集而不是值分配给随机结果来推广标准概率论。本文的贡献有两个方面:首先,我们介绍了物理层考虑因素在评估逻辑发现算法性能方面的现实效果;这样的介绍对于准确评估算法的执行方式是必要的。其次,考虑到环境的双重不确定性(即缺乏对邻居数目的了解以及对单个信号参数的了解),我们采用RST的观点,并证明了其相对于经典匹配滤波器的优势检测方法。

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