文章基本信息

标题：Second-Order Kalman Filtering Application to Fading Channels Supported by Real Data
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作者：Azra Kapetanovic ; Redhwan Mawari ; Mohamed A. Zohdy 等
期刊名称：Journal of Signal and Information Processing
印刷版ISSN：2159-4465
电子版ISSN：2159-4481
出版年度：2016
卷号：07
期号：02
页码：61-74
DOI：10.4236/jsip.2016.72008
语种：English
出版社：Scientific Research Publishing
摘要：The lack of effective techniques for estimation of shadow power in fading mobile wireless communication channels motivated the use of Kalman Filtering as an effective alternative. In this paper, linear second-order state space Kalman Filtering is further investigated and tested for applicability. This is important to optimize estimates of received power signals to improve control of handoffs. Simulation models were used extensively in the initial stage of this research to validate the proposed theory. Recently, we managed to further confirm validation of the concept through experiments supported by data from real scenarios. Our results have shown that the linear second-order state space Kalman Filter (KF) can be more accurate in predicting local shadow power profiles than the first-order Kalman Filter, even in channels with imposed non-Gaussian measurement noise.
关键词：Kalman Filtering;Rayleigh;Gaussian;Multipath;Shadowing;Power Estimation