Distortion minimization via adaptive digital and analog transmission for energy harvesting-based wireless sensor networks

This paper studies wireless sensor networks with energy harvesting in which a transmitter collects the observed source signals from the sensors and send to a fusion center using the energy harvested from an ambient environment. The main objective is to minimize the distortion between the source signal observed by the sensors and that recovered by the fusion center. We introduce a novel adaptive transmission approach in which the transmitter can use either analog or digital transmission according to the dynamics of the energy harvesting process. We formulate the optimization problem as a Markov decision process (MDP) and derive the optimal policy that can minimize the long-term discounted distortion for the fusion center. Numerical results show that our proposed approach can significantly improve the network performance under different situations.