非平稳与非完美通信条件下的CI分布式算法

CI Distributed Algorithm under Non-stationary and Imperfect Communication Conditions

在无线传感网中,传感节点需从物理世界中估计一些兴趣参数,因此分布式估计是一个重要问题.为解决这一问题,该文发展了CI(consensus-plus-innovations)分布式算法,并从理论上分析了非平稳条件及非完美通信条件下CI分布式算法的均值收敛性能,说明CI分布式算法是均值收敛的,此外还分析了算法的渐进正态性.研究表明,非平稳条件和非完美通信条件并不影响CI算法的收敛性和渐进正态性,但会影响渐进方差.通过仿真验证了CI分布式算法的合理性.

In wireless sensor networks, distributed estimation is an important issue, in which sensor nodes estimate parameters of interest from the physical world. This paper develops a consensus-plus-innovations （CI） distributed algorithm to deal with distributed estimation. The focus is on the mean convergence performance of a CI distributed algo- rithm under non-stationary and imperfect communication conditions. Theoretical analysis shows that the algorithm is mean convergent and has an asymptotic normality property. Also, non-stationarity and imperfect communication conditions have no effect on the mean convergence performance and asymptotic normMity. However, these conditions have an impact on the asymptotic variance of the algorithm. Validity of the CI distributed algo- rithm is shown by simulation.