Syndrome-based Fusion Rules in Heterogeneous Distributed Quickest Change Detection
<|reference_start|>Syndrome-based Fusion Rules in Heterogeneous Distributed Quickest Change Detection: In this paper, the heterogeneous distributed quickest change detection (HetDQCD) with 1-bit non-anonymous feedback is studied. The concept of syndromes is introduced and the family of syndrome-based fusion rules is proposed, which encompasses all deterministic fusion rules as special cases. Through the Hasse diagram of syndromes, upper and lower bounds on the second-order performance of expected detection delay as a function of average run length to false alarm are provided. An interesting instance, the weighted voting rule previously proposed in our prior work, is then revisited, for which an efficient pruning method for breadth-first search in the Hasse diagram is proposed to analyze the performance. This in turn assists in the design of the weight threshold in the weighted voting rule. Simulation results corroborate that our analysis is instrumental in identifying a proper design for the weighted voting rule, demonstrating consistent superiority over both the anonymous voting rule and the group selection rule in HetDQCD.<|reference_end|>
@article{li2024syndrome-based,
    title={Syndrome-based Fusion Rules in Heterogeneous Distributed Quickest Change
  Detection},
    author={Wen-Hsuan Li and Yu-Chih Huang},
    journal={arXiv preprint arXiv:2405.06933},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.06933},
    primaryClass={cs.IT math.IT}
}