Future Internet-of-Things (IoT) will connect billions of small computingdevices embedded in the environment and support their device-to-device (D2D)communication. Powering this massive number of embedded devices is a keychallenge of designing IoT since batteries increase the devices' form factorsand their recharging/replacement is difficult. To tackle this challenge, wepropose a novel network architecture that integrates wireless power transferand backscatter communication, called wirelessly powered backscattercommunication (WP-BC) networks. In this architecture, power beacons (PBs) aredeployed for wirelessly powering devices; their ad-hoc communication relies onbackscattering and modulating incident continuous waves from PBs, whichconsumes orders-of-magnitude less power than traditional radios. Thereby, thedense deployment of low-complexity PBs with high transmission power can power alarge-scale IoT. In this paper, a WP-BC network is modeled as a random Poissoncluster process in the horizontal plane where PBs are Poisson distributed andactive ad-hoc pairs of backscatter communication nodes with fixed separationdistances form random clusters centered at PBs. Furthermore, by harvestingenergy from and backscattering radio frequency (RF) waves transmitted by PBs,the transmission power of each node depends on the distance from the associatedPB. Applying stochastic geometry, the network coverage probability andtransmission capacity are derived and optimized as functions of the backscatterduty cycle and reflection coefficient as well as the PB density. The effects ofthe parameters on network performance are characterized.
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