Cross-layer design of distributed sensing-estimation with quality feedback, Part I: Optimal schemes

摘要

This two-part paper presents a feedback-based cross-layer framework fordistributed sensing and estimation of a dynamic process by a wireless sensornetwork (WSN). Sensor nodes wirelessly communicate measurements to the fusioncenter (FC). Cross-layer factors such as packet collisions and thesensing-transmission costs are considered. Each SN adapts itssensing-transmission action based on its own local observation quality and theestimation quality feedback from the FC under cost constraints for each SN. Inthis first part, the optimization complexity is reduced by exploiting thestatistical symmetry and large network approximation of the WSN. Structuralproperties of the optimal policy are derived for a coordinated and adecentralized scheme. It is proved that a dense WSN provides sensing diversity,so that only a few SNs with the best local observation quality need to beactivated, despite the fluctuations of the WSN. The optimal policy dictatesthat, when the estimation quality is poor, only the best SNs activate,otherwise all SNs remain idle to preserve energy. The costs of coordination andfeedback are evaluated, revealing the scalability of the decentralized schemeto large WSNs, at the cost of performance degradation. Simulation resultsdemonstrate cost savings from 30% to 70% over a non-adaptive scheme, andsignificant gains over a previously proposed estimator which does not considerthese cross-layer factors.