  In this paper, we study the rate-power region of a simultaneous wireless
information and power transfer (SWIPT) system where a transmitter (TX)
broadcasts a common signal to an information receiver (IR) and an energy
harvester (EH). Since practical EH circuits include a reactive element as part
of their signal rectifier and the voltage on this element cannot drop or rise
instantaneously, the EH circuit has memory. We model the memory effect of the
EH by a Markov reward chain. Furthermore, since an analytical model that
includes all non-linear and memory effects of the EH circuit is not available,
we employ a deep neural network (DNN) to model the Markov chain evolution. We
formulate an optimization problem to determine the rate-power region of the
considered SWIPT system and propose an iterative algorithm based on sequential
quadratic programming (SQP) to solve it. Our numerical results show that the
optimal input distribution and the rate-power region depend on both the input
power level at the EH and the symbol duration.
