Repeated game for distributed estimation in autonomous wireless sensor networks

The power scheduling problem for distributed estimation in autonomous wireless sensor networks (WSNs) poses a vital problem of nodes´ selfishness. Each node autonomously decides whether or not to transmit their observations to the fusion center (FC), and not be controlled by the fusion center (FC) any more. To encourage cooperation within selfish nodes and improve the final estimation accuracy, a repeated game based on a punishment mechanism is proposed to self-enforce nodes´ behaviors. A Nash equilibrium strategy is discussed and numerical results validate the effectiveness of the proposed repeated game.