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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Wireless Powered Cognitive Radio Networks with Compressive Sensing and Matrix Completion
AU - Qin, Zhijin
AU - Liu, Yuanwei
AU - Gao, Yue
AU - Elkashlan, Maged
AU - Nallanathan, Arumugam
N1 - ©2017 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
PY - 2017/4
Y1 - 2017/4
N2 - In this paper, we consider cognitive radio networks in which energy constrained secondary users (SUs) can harvest energy from the randomly deployed power beacons. A new frame structure is proposed for the considered networks. In the considered network, a wireless power transfer model is proposed, and the closed-form expressions for the power outage probability are derived. In addition, in order to reduce the energy consumption at SUs, sub-Nyquist sampling are performed at SUs. Subsequently, compressive sensing and matrix completion techniques are invoked to recover the original signals at the fusion center by utilizing the sparsity property of spectral signals. Throughput optimizations of the secondary networks are formulated into two linear constrained problems, which aim to maximize the throughput of a single SU and the whole cooperative network, respectively. Three methods are provided to obtain the maximal throughput of secondary networks by optimizing the time slots allocation and the transmit power. Simulation results show that the maximum throughput can be improved by implementing compressive spectrum sensing in the proposed frame structure design.
AB - In this paper, we consider cognitive radio networks in which energy constrained secondary users (SUs) can harvest energy from the randomly deployed power beacons. A new frame structure is proposed for the considered networks. In the considered network, a wireless power transfer model is proposed, and the closed-form expressions for the power outage probability are derived. In addition, in order to reduce the energy consumption at SUs, sub-Nyquist sampling are performed at SUs. Subsequently, compressive sensing and matrix completion techniques are invoked to recover the original signals at the fusion center by utilizing the sparsity property of spectral signals. Throughput optimizations of the secondary networks are formulated into two linear constrained problems, which aim to maximize the throughput of a single SU and the whole cooperative network, respectively. Three methods are provided to obtain the maximal throughput of secondary networks by optimizing the time slots allocation and the transmit power. Simulation results show that the maximum throughput can be improved by implementing compressive spectrum sensing in the proposed frame structure design.
U2 - 10.1109/TCOMM.2016.2623606
DO - 10.1109/TCOMM.2016.2623606
M3 - Journal article
VL - 65
SP - 1464
EP - 1476
JO - IEEE Transactions on Communications
JF - IEEE Transactions on Communications
SN - 0090-6778
IS - 4
ER -