2013/09/27 by Yuzhe Li, Daniel E. Quevedo, Vincent K. N. Lau +2 · 1 citation
Computer Science · #Age of Information Optimization #Distributed Sensor Networks and Detection Algorithms #Energy Efficient Wireless Sensor Networks
paper · doi:10.1109/tsp.2013.2283838
openalex publication_date 2013/09/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/02
We consider periodic sensor transmission power allocation with an average energy constraint. The sensor sends its Kalman filter-based state estimate to the remote estimator through an unreliable link. Dropout probabilities depend on the power level used. To encompass applications where the estimator needs to attend to multiple tasks, we allow for irregular sampling, following a periodic pattern. Using properties of an underlying Markov chain model, we derive an explicit expression for the estimation error covariance. The results are then used to study optimal sensor power scheduling which minimizes the average error covariance.