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In this paper, we consider a cognitive radio network in which energyconstrained secondary users (SUs) can harvest energy from the randomly deployedpower beacons (PBs). A new frame structure is proposed for the considerednetwork. A wireless power transfer (WPT) model and a compressive spectrumsensing model are introduced. In the WPT model, a new WPT scheme is proposed,and the closed-form expressions for the power outage probability are derived.In compressive spectrum sensing model, two scenarios are considered: 1) SingleSU, and 2) Multiple SUs. In the single SU scenario, in order to reduce theenergy consumption at the SU, compressive sensing technique which enablessub-Nyquist sampling is utilized. In the multiple SUs scenario, cooperativespectrum sensing (CSS) is performed with adopting low-rank matrix completiontechnique to obtain the complete matrix at the fusion center. Throughputoptimizations of the secondary network are formulated into two linearconstrained problems, which aim to maximize the throughput of single SU and theCSS networks, respectively. Three methods are provided to obtain the maximalthroughput of secondary network by optimizing the time slots allocation and thetransmit power. Simulation results show that: 1) Multiple SUs scenario canachieve lower power outage probability than single SU scenario; and 2) Theoptimal throughput can be improved by implementing compressive spectrum sensingin the proposed frame structure design.

Throughput Analysis of Wireless Powered Cognitive Radio Networks with Compressive Sensing and Matrix Completion