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In this paper, we study the rate-power region of a simultaneous wirelessinformation and power transfer (SWIPT) system where a transmitter (TX)broadcasts a common signal to an information receiver (IR) and an energyharvester (EH). Since practical EH circuits include a reactive element as partof their signal rectifier and the voltage on this element cannot drop or riseinstantaneously, the EH circuit has memory. We model the memory effect of theEH by a Markov reward chain. Furthermore, since an analytical model thatincludes 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. Weformulate an optimization problem to determine the rate-power region of theconsidered SWIPT system and propose an iterative algorithm based on sequentialquadratic programming (SQP) to solve it. Our numerical results show that theoptimal input distribution and the rate-power region depend on both the inputpower level at the EH and the symbol duration.

Rate-Power Region of SWIPT Systems Employing Nonlinear Energy Harvester Circuits with Memory