Adaptive Quantization for Distributed Estimation in Energy-Harvesting Wireless Sensor Networks: A Game-Theoretic Approach

The problem of distributed estimation in energy-harvesting wireless sensor networks (EH-WSNs) is studied. In general, the energy state of an energy-harvesting sensor varies dramatically. Existing efforts mainly concentrate on the problem of distributed estimation for battery-powered WSNs, ignoring the crucial issue of energy harvesting. Therefore, the unpredictable energy harvesting, the energy storage device, and energy consumption are modeled in a unified way to jointly address the energy harvesting and distributed estimation problem. In this paper, combining with the classical adaptive distributed estimation scheme, the problem of parameter estimation in EH-WSNs is formulated as a game of complete and perfect information. Each player decides its strategy according to the others' energy states and actions. The subgame perfect equilibrium (SPE) is derived by backward induction. Simulation results show that the proposed SPE makes full use of the harvested energy and improves the estimation performance.