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- W3100899678 abstract "In this paper, we study data-aided sensing (DAS) for distributed detection in wireless sensor networks (WSNs) when sensors' measurements are correlated. In particular, we derive a node selection criterion based on the J-divergence in DAS for reliable decision subject to a decision delay constraint. Based on the proposed J-divergence based DAS, the nodes can be selected to rapidly increase the log-likelihood ratio (LLR), which leads to a reliable decision with a smaller number of the sensors that upload measurements for a shorter decision delay. From simulation results, it is confirmed that the J-divergence based DAS can provide a reliable decision with a smaller number of sensors compared to other approaches." @default.
- W3100899678 created "2020-11-23" @default.
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- W3100899678 date "2020-11-17" @default.
- W3100899678 modified "2023-09-27" @default.
- W3100899678 title "Data-aided Sensing for Distributed Detection" @default.
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