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<p>In wireless network scenarios, the probability of packet loss is significantly affected by the length of data packets. To address this challenge, channel scheduling protocols are often adopted to reduce packet size by allowing only a limited number of nodes to transmit at each instant. Motivated by this, we study the distributed filtering problem for time-varying complex networks where data transmission is governed by multi-component round-robin protocols (MCRRPs) and affected by random packet dropouts. The MCRRP is deployed with a Bernoulli lossy network. By examining the correlation between the number of sensor components broadcast by each node and the probability of packet arrival, the traditional round-robin protocol is expanded to incorporate multiple components. For the purpose of leveraging and establishing suitable requirements, the set-membership technique and the stochastic analysis are utilized. These conditions guarantee that the estimation errors simultaneously meet the requirement of being inside an ellipsoidal constraint and achieve finite horizon <i>H</i><sub>∞</sub> performance. Subsequently, a novel set of criteria is established to ensure the fulfillment of multiple metrics by iteratively solving matrix inequalities under certain conditions. Finally, numerical simulations are presented to validate the effectiveness of the proposed distributed filtering method.</p>

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Distributed Filtering for Complex Networks Under Multi-component Round-robin Protocol and Packet-length-dependent Lossy Network

  • 期刊论文

  • 发表日期：

    2025年6月11日

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  • Shibing Hu,
  • Shengqi Lu,
  • Yuewu Song,
  • Miaochao Chen

摘要

In wireless network scenarios, the probability of packet loss is significantly affected by the length of data packets. To address this challenge, channel scheduling protocols are often adopted to reduce packet size by allowing only a limited number of nodes to transmit at each instant. Motivated by this, we study the distributed filtering problem for time-varying complex networks where data transmission is governed by multi-component round-robin protocols (MCRRPs) and affected by random packet dropouts. The MCRRP is deployed with a Bernoulli lossy network. By examining the correlation between the number of sensor components broadcast by each node and the probability of packet arrival, the traditional round-robin protocol is expanded to incorporate multiple components. For the purpose of leveraging and establishing suitable requirements, the set-membership technique and the stochastic analysis are utilized. These conditions guarantee that the estimation errors simultaneously meet the requirement of being inside an ellipsoidal constraint and achieve finite horizon H∞ performance. Subsequently, a novel set of criteria is established to ensure the fulfillment of multiple metrics by iteratively solving matrix inequalities under certain conditions. Finally, numerical simulations are presented to validate the effectiveness of the proposed distributed filtering method.