摘要
针对无线体域网(WBAN)节点电池能量有限和不易更换电源的问题,提出一种基于稀释表示分类算法的节点休眠策略(NSS-SRC)。当WBAN节点采集的人体生理信号处于正常范围时,采用稀疏表示理论对测试样本信号进行识别,根据识别结果滤除不需要传送的正常信号,将WBAN节点转换为休眠状态,并延长节点休眠时间,从而减少节点数据传输量。通过NS2软件对节点延时和能耗进行仿真分析,结果表明,在生理信号通常处于稳定范围的WBAN中,与传统TDMA,BCMAC相比,NSS-SRC策略能有效降低能耗和延时。
Since the battery energy of wireless body area network(WBAN)node is limited,and its power supply is hard toreplace,a node sleep strategy based on sparse representation classification(NSS-SRC)algorithm is proposed.While the humanbody physiological signal collected by WBAN nodes stays in the normal range,the sparse representation theory is used to identify the test sample signals.According to the identification results,the normal signals which needn′t to be sent are filtered out,and the state of WBAN node is converted into the sleep state.The node sleep time is prolonged to reduce the transmission quantity of node data.The node delay and energy consumption are simulated and analyzed with NS2software.The results show that,in comparison with the traditional TDMA and BCMAC algorithms,the NSS-SRC strategy can reduce the energy consumption andtime delay effectively while the physiological signal is in WBAN with stable range.
作者
陈家顺
周岳斌
王涛
CHEN Jiashun;ZHOU Yuebin;WANG Tao(School of Machinery and Automation,Wuhan University of Science and Technology,Wuhan 430081,China;School of Mechanical & Auto Engineering,Hubei University of Arts & Science,Xiangyang 441053,China;The Collaborative Innovation Center of Hubei Province for Auto Parts Manufacturing Equipment Digitization,Xiangyang 441053,China)
出处
《现代电子技术》
北大核心
2017年第17期15-19,共5页
Modern Electronics Technique
基金
湖北省自然科学基金项目(2015CFC802)
襄阳市研究与开发计划项目(襄科计[2014]12号)
汽车零部件制造装备数字化湖北省协同创新中心开放课题项目(hbuascic2014017)
"机电汽车"湖北省优势特色学科群开放课题项目(XKQ2016022)
关键词
WBAN
休眠策略
稀疏表示
节能
WBAN
sleep strategy
sparse representation
energy saving
