TY - JOUR
T1 - Distributed detection of sparse signals with censoring sensors in clustered sensor networks
AU - Li, Chengxi
AU - Li, Gang
AU - Varshney, Pramod K.
N1 - Funding Information:
This work was supported in part by National Natural Science Foundation of China under Grants 61790551 and 61925106 , and in part by the National Science Foundation of USA under Grant No. ENG 60064237 .
Publisher Copyright:
© 2022
PY - 2022/7
Y1 - 2022/7
N2 - In this paper, we explore the distributed detection of sparse signals in energy-limited clustered sensor networks (CSNs). For this problem, the centralized detector based on locally most powerful test (LMPT) methodology that uses the analog data transmitted by all the sensor nodes in CSNs can be easily realized according to the prior work. However, for the centralized LMPT detector, the energy consumption caused by data transmission is excessively high, which makes its implementation in CSNs with limited energy supply impractical. To address this issue, we propose a new detector by combining the advantages of censoring and LMPT strategies, in which both the cluster head (CLH) nodes and the ordinary (ORD) nodes only send data deemed to be informative enough and the fusion center (FC) fuses the received data based on LMPT methodology. The detection performance of the proposed detector, characterized by Fisher Information, is analyzed in the asymptotic regime. Also, we analytically derive the relationship between the detection performance of the proposed censoring-based LMPT (cens-LMPT) detector and the communication rates, both of which are controlled by the censoring thresholds. We present an illustrative example by considering the detection problem with 2-CSNs, i.e., CSNs in which each cluster contains two nodes, and provide corresponding theoretical analysis and simulation results.
AB - In this paper, we explore the distributed detection of sparse signals in energy-limited clustered sensor networks (CSNs). For this problem, the centralized detector based on locally most powerful test (LMPT) methodology that uses the analog data transmitted by all the sensor nodes in CSNs can be easily realized according to the prior work. However, for the centralized LMPT detector, the energy consumption caused by data transmission is excessively high, which makes its implementation in CSNs with limited energy supply impractical. To address this issue, we propose a new detector by combining the advantages of censoring and LMPT strategies, in which both the cluster head (CLH) nodes and the ordinary (ORD) nodes only send data deemed to be informative enough and the fusion center (FC) fuses the received data based on LMPT methodology. The detection performance of the proposed detector, characterized by Fisher Information, is analyzed in the asymptotic regime. Also, we analytically derive the relationship between the detection performance of the proposed censoring-based LMPT (cens-LMPT) detector and the communication rates, both of which are controlled by the censoring thresholds. We present an illustrative example by considering the detection problem with 2-CSNs, i.e., CSNs in which each cluster contains two nodes, and provide corresponding theoretical analysis and simulation results.
KW - Censoring
KW - Clustered sensor networks
KW - Distributed detection
KW - Locally most powerful tests
KW - Sparse signals
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U2 - 10.1016/j.inffus.2022.03.002
DO - 10.1016/j.inffus.2022.03.002
M3 - Article
AN - SCOPUS:85127145650
SN - 1566-2535
VL - 83-84
SP - 1
EP - 18
JO - Information Fusion
JF - Information Fusion
ER -