文章基本信息

标题：Threshold Selection Algorithm Based on Skewness and Standard Deviation Using Back Propagation Artificial Neural Networks in the 60GHz Wireless Communication Systems
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作者：Xiao-Lin Liang ; Hao Zhang ; Ting-Ting Lu 等
期刊名称：International Journal of Smart Home
印刷版ISSN：1975-4094
出版年度：2016
卷号：10
期号：2
页码：245-278
DOI：10.14257/ijsh.2016.10.2.23
出版社：SERSC
摘要：Accurate localization has gained significant interest in the field of sensor networks, impulse radio 60GHz signals which is low cost, low complexity are even much more practical for ranging, localization and tracking systems because of the high time and multipath resolution and so on. Typically, accurate Time of Arrival (TOA) estimation of the 60GHz signals is very important. In order to improve the precision of the TOA estimation, a new threshold selection algorithm using Back Propagation Artificial Neural Networks (BP-ANN) is proposed which is based on a joint metric of Skewness and Standard Deviation after Energy Detection. The best threshold based on the signal-to-noise ratio (SNR) is investigated and the effects of the integration period and channel model are examined. Simulation results are presented which show that for the IEEE802.15.3c channel models CM1.1 and CM2.1, the proposed BP-ANN algorithm provides better precision and robustness in both high and low SNR environments than other ED-based algorithms.
关键词：60GHz; TOA estimation; BP-ANN; Skewness; Standard Deviation