Proceedings Article10.1109/GLOBALSIP.2015.7418218
Multi-sensor generalized sequential probability ratio test using level-triggered sampling
Shang Li,Xiaoou Li,Xiaodong Wang,Jingchen Liu +3 more
- 01 Dec 2015
- pp 363-367
TL;DR: The proposed LTS-GSPRT amounts to the algorithm where each sensor successively reports the decisions of local GSPRTs to the fusion center to preserve the same asymptotic performance of the centralized GSRPT as the local thresholds and global thresholds grow large at different rates.
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Abstract: 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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