A Novel Distributed Resource Allocation Scheme for Wireless Powered Cognitive Radio Internet of Things Networks

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 protocol called Distributed Max-min Rate with Cognitive Radio (D-MRCR) for use by devices and PBs. Devices set their operation mode using local information and use a game theory based approach to iteratively adjust their transmit power. On the other hand, each PB employs a Linear Program (LP) to determine its beamforming vector. Our results show that the max-min rate of D-MRCR is within 51.84% that of MILP