期刊
IEEE TRANSACTIONS ON SIGNAL PROCESSING
卷 66, 期 2, 页码 528-539出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSP.2017.2773429
关键词
Linear inverse problem; sensor placement; sensor scheduling; binary optimization; convex relaxation; energy constraints; communications constraints
资金
- Engineering and Physical Sciences Research Council (EPSRC) [EP/K014277/1]
- MOD University Defence Research Collaboration (UDRC) on Signal Processing
- EPSRC [EP/K014277/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/K014277/1] Funding Source: researchfish
In this paper, we present new algorithms and analysis for the linear inverse sensor placement and scheduling problems over multiple time instances with power and communications constraints. The proposed algorithms, which deal directly with minimizing the mean squared error (MSE), are based on the convex relaxation approach to address the binary optimization scheduling problems that are formulated in sensor network scenarios. We propose to balance the energy and communications demands of operating a network of sensors over time while we still guarantee a minimum level of estimation accuracy. We measure this accuracy by the MSE for which we provide average case and lower bounds analyses that hold in general, irrespective of the scheduling algorithm used. We show experimentally how the proposed algorithms perform against state-of-the-art methods previously described in the literature.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据