Throughput analysis for compressive spectrum sensing with wireless power transfer

Abstract

In this paper, we consider a cognitive radio network in which energy constrained secondary users (SUs) can harvest energy from the randomly deployed power beacons. A new frame structure with four time slots, namely, energy harvesting, spectrum sensing, energy harvesting and data transmission is proposed. In the energy harvesting slot, a new wireless power transfer (WPT) scheme in a bounded power transfer model is proposed to enable power SUs wirelessly. Closed-form expression for the power outage probability of the proposed WPT scheme is derived. In the spectrum sensing slot, we propose to utilize the compressive sensing technique which enables sub-Nyquist sampling to further reduce the energy consumption at SUs. Throughput of the secondary network with the proposed frame structure is formulated into a nonlinear constraint problem. Three optimization methods are provided to obtain the maximal throughput of secondary network by optimizing the time slots allocation and the transmit power of SUs.