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Interference of human's ankle to the channel characteristics of near surface WUSN

Interference of human's ankle to the channel characteristics of near surface WUSN

作     者:LI Li WU Wei CHEN Jian-ya LIU Yun-jie 

作者机构:State Key Laboratory of Networking and Switching TechnologyBeijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and ConvergenceBeijing University of Posts and Telecommunications 

出 版 物:《The Journal of China Universities of Posts and Telecommunications》 (中国邮电高校学报(英文版))

年 卷 期:2014年第21卷第1期

页      面:36-42页

核心收录:

学科分类:080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 0809[工学-电子科学与技术(可授工学、理学学位)] 080202[工学-机械电子工程] 08[工学] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 081001[工学-通信与信息系统] 0802[工学-机械工程] 

基  金:supported by the National Natural Science Foundation of China(61001120) 

主  题:WUSN lateral wave human tissue path loss model EM wave attenuation 

摘      要:Because of its potential applications in agriculture, environment monitoring and so on, wireless underground sensor network(WUSN) has been researched more and more extensively in recent years. The main and most important difference of WUSN to terrestrial wireless sensor network(WSN) is the channel characteristics, which determines the design methodology of it. In this paper, the propagation character of electromagnetic(EM) wave in the near surface WUSN is analyzed, as well as the path loss model of it is given. In addition, the influence of human's ankle to the channel characteristics of near surface WUSN is investigated by electromagnetic theory analysis, simulation and experiment. A novel path loss model of near surface WUSN which takes the interference of human's ankle into consideration is proposed. It is verified that the existing of human above the WUSN system may cause additional attenuation to the signal of near surface WUSN which propagates as lateral wave along the ground. Moreover, the relation of the attenuation and operating frequency is deduced, which gives a reference to extend the frequency band applied in WUSN.

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