LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Data-Aided Sensing for Distributed Detection

Photo from wikipedia

In this letter, 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… Click to show full abstract

In this letter, 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.

Keywords: aided sensing; data aided; distributed detection; reliable decision; decision

Journal Title: IEEE Wireless Communications Letters
Year Published: 2021

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.