The technology of simultaneous wireless information and power transfer (SWIPT)enables the transmission and reception of both information and power simultaneously.
It typically adopts a separate receiver (SR) architecture that employs separatemodules f...
The technology of simultaneous wireless information and power transfer (SWIPT)enables the transmission and reception of both information and power simultaneously.
It typically adopts a separate receiver (SR) architecture that employs separatemodules for information decoding (ID) and energy harvesting (EH) by means oftime- or power-splitting techniques. However, the SR architecture faces limitationsfor adoption by ultra-low-power Internet-of-Things (IoT) sensors due to its highenergy consumption during the ID process. To address these limitations, research isunderway on an integrated receiver (IR) architecture for SWIPT and, accordingly,novel modulation schemes. However, there is a lack of research on schedulingbetween a couple of modulation schemes designed and tailored for IR architecturesin SWIPT-based IoT sensor networks. Therefore, in this paper, we aim to addressa scheduling problem that achieves a high average system data throughput in sucha SWIPT-based IoT sensor network while guaranteeing a given minimum averageharvested energy amount and data throughput for each IoT sensor. Leveragingstochastic programming theory, we propose an algorithm that jointly schedules IoTsensors and modulation schemes. Lastly, we demonstrate the superiority of ourapproach through simulation results.