A decentralized framework for linear coherent estimation with spatial collaboration

We study an estimation problem where a fusion center estimates a random parameter by using a partially connected network of sensor nodes. The process involves two stages. In the collaboration stage, the sensor nodes share their observations with their neighbors. In the estimation stage, all the sensor nodes form a coherent beam to the fusion center using the analog amplify-and-forward procedure. In the previous work of Kar and Varshney (2013) on this topic, a control center determines the optimum collaboration strategy that is sent to the sensor nodes prior to starting the two-stage procedure. In this paper, we develop a new framework where the collaboration strategies are computed in a decentralized manner using minimal communication with the control center. This makes the sensor network more energy efficient and reduces control channel communication requirements.