Throughput Analysis for Compressive Spectrum Sensing with Wireless Power Transfer

Zhijin Qin, Yuanwei Liu, Yue Gao, Maged Elkashlan, Arumugam Nallanathan

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

6 Citations (Scopus)


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.
Original languageEnglish
Title of host publication2015 IEEE Global Communications Conference (GLOBECOM)
Publication statusPublished - Dec 2015


Dive into the research topics of 'Throughput Analysis for Compressive Spectrum Sensing with Wireless Power Transfer'. Together they form a unique fingerprint.

Cite this