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Multi-Sensor Generalized Sequential Probability Ratio Test Using Level-Triggered Sampling

Citation Author(s):
Xiaoou Li;Xiaodong Wang;Jingchen Liu
Submitted by:
Shang LI
Last updated:
2 June 2016 - 1:58pm
Document Type:
Presentation Slides
Document Year:
2015
Event:
Presenters:
Shang Li
 

This paper investigates the generalized sequential probability ratio test (GSPRT) with multiple sensors. Focusing on the communication-constrained scenario, where sensors transmit one-bit messages to the fusion center, we propose a decentralized GSRPT based on level-triggered sampling scheme (LTS-GSPRT). The proposed LTS-GSPRT amounts to the algorithm where each sensor successively reports the decisions of local GSPRTs to the fusion center. Interestingly, with significantly lower communication overhead, LTS-GSPRT preserves the same asymptotic performance of the centralized GSPRT as the local thresholds and global thresholds grow large at different rates.

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