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This paper studies sample delivery in a multi-hop network where a power beacon charges devices via radio frequency (RF) signals. Devices forward samples with a deadline from a source to a sink. The goal is to minimize the power beacon’s transmit power and guarantee that samples arrive at the sink with probability (1-) by their deadline, where is a given probability of failure. A key challenge is that the power beacon does not have instantaneous channel gains information to devices and also between devices; i.e., it does not know the energy level of devices. To this end, we formulate a chance...

This paper studies data collection in a wireless powered Internet of things (IoT) network with a hybrid access point (HAP). A fundamental problem at the HAP is to determine the number of time slots over a given planning horizon that is used to charge and collect data from devices. To this end, we outline a mixed integer linear program (MILP) to determine (i) the mode (charge or data) of each slot, (ii) the HAP’s transmit power allocation, and (iii) transmitting devices in data slots. Further, we propose a receding horizon approach whereby the HAP solves the said MILP over a time window using...

Abstract This paper considers a novel Internet of Things (IoT) network comprising of sensor devices and Power Beacons (PBs); both types of nodes are equipped with a Cognitive Radio (CR). In addition, these sensor devices are powered by Radio Frequency (RF) signals from PBs. Our aim is to maximize the minimum rate of devices acting as sources. We outline the first Mixed Integer Linear Program (MILP) that jointly optimizes the channel assignment of PBs and devices, beamforming vector of PBs, data routing over multiple hops and link activation schedule of devices. We also design a distributed pr...