arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1509.09282cs.ITcs.DCmath.IT
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衰落信道下具有间歇测量的中继辅助传感器网络分布式推理

Distributed Inference for Relay-Assisted Sensor Networks With Intermittent Measurements Over Fading Channels

Shanying Zhu, Yeng Chai Soh, Lihua Xie

摘要:

在本文中,我们考虑一个一般的分布式估计问题,在中继辅助传感器网络考虑到时变的非对称通信,衰落信道和间歇性测量。受集中式滤波算法的启发,本文提出了一种基于新息的分布式估计算法,该算法结合了测量新息(同化新测量)和局部数据新息(合并邻近数据)。我们的算法是完全分布式的,不需要一个融合中心。我们建立的理论结果,所提出的算法的渐近无偏性和一致性。具体而言,为了应对时变的非对称通信,我们利用排序技术和广义Perron补操纵一阶矩和二阶矩分析在一个易于处理的框架。此外,我们提出了一个面向性能的设计,所提出的算法的能量受限网络的理论结果的基础上。仿真结果证实了理论研究结果,从而证明了所提出的算法的有效性。

英文摘要:

In this paper, we consider a general distributed estimation problem in relay-assisted sensor networks by taking into account time-varying asymmetric communications, fading channels and intermittent measurements. Motivated by centralized filtering algorithms, we propose a distributed innovation-based estimation algorithm by combining the measurement innovation (assimilation of new measurement) and local data innovation (incorporation of neighboring data). Our algorithm is fully distributed which does not need a fusion center. We establish theoretical results regarding asymptotic unbiasedness and consistency of the proposed algorithm. Specifically, in order to cope with time-varying asymmetric communications, we utilize an ordering technique and the generalized Perron complement to manipulate the first and second moment analyses in a tractable framework. Furthermore, we present a performance-oriented design of the proposed algorithm for energy-constrained networks based on the theoretical results. Simulation results corroborate the theoretical findings, thus demonstrating the effectiveness of the proposed algorithm.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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