Abstract
This article considers data collection in a wireless-powered Internet-of-Things (IoT) network. Specifically, it addresses the novel problem of determining the mode of each time slot, where a hybrid access point (HAP) needs to decide whether to charge or collect data from devices. Also, in data time slots, HAP has to decide on a device for data transmission. To this end, we outline an integer linear program (ILP) to determine the mode and the transmitting device over a given planning time horizon. We also propose a rolling horizon (RollH) approach that uses a Gaussian mixture model (GMM) to estimate channel gains. Our results indicate that the amount of data collected by HAP is affected by its charging power, distance between HAP and each device, number of devices, and planning horizon length. The RollH approach allows the HAP to collect 740% more data as compared to competing approaches.
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