无线传感器网络中存在丢包的分布式估计
Distributed Estimation over Wireless Sensor Networks with Packet Losses
摘要：
设计并分析了一种分布式自适应算法，用于估计无线传感器网络测量的时变信号。该算法的主要特点之一是，没有中央协调节点之间需要被假定。网络中的节点所进行的测量受到噪声的影响，并且节点之间的通信容易发生数据包丢失。节点与相邻节点交换本地估计和测量。网络的每个节点局部地计算最小化估计误差方差的自适应权重。分散条件的权重，需要在整个网络的估计误差的收敛，提出。一个Lipschitz优化问题，以保证稳定性和最小化的方差。一个有效的策略来分配最优解的计算。在存在完美链路和有损耗链路的情况下对分布式算法进行了理论性能分析。数值模拟说明了各种网络拓扑结构和数据包丢失概率的性能。
英文摘要：
A distributed adaptive algorithm to estimate a time-varying signal, measured by a wireless sensor network, is designed and analyzed. One of the major features of the algorithm is that no central coordination among the nodes needs to be assumed. The measurements taken by the nodes of the network are affected by noise, and the communication among the nodes is subject to packet losses. Nodes exchange local estimates and measurements with neighboring nodes. Each node of the network locally computes adaptive weights that minimize the estimation error variance. Decentralized conditions on the weights, needed for the convergence of the estimation error throughout the overall network, are presented. A Lipschitz optimization problem is posed to guarantee stability and the minimization of the variance. An efficient strategy to distribute the computation of the optimal solution is investigated. A theoretical performance analysis of the distributed algorithm is carried out both in the presence of perfect and lossy links. Numerical simulations illustrate performance for various network topologies and packet loss probabilities.
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