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Optimization in Cognitive Radio Networks with SWIPT-Based DF Relay

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Abstract

Energy-constrained relay networks are normally powered by a fixed energy, which limits the runtime of networks. Energy harvesting (EH) with simultaneous wireless information and power transfer (SWIPT) is hopeful to increase the life of energy-limited relay networks. We investigate the optimization problem about power splitting ratio for SWIPT-based decode-and-forward (DF) relay in cognitive radio networks (CRNs). Secondary relaying node (SRN) harvests energy from secondary source node (SSN) then use the energy to assist forwarding SSN information to the secondary destination node (SDN). We maximize throughput of secondary users (SUs) if the interference caused by SU to the primary users (PUs) is under the threshold. Some opinions are provided through theory analysis and simulation results.

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Correspondence to Jie Zhang .

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Zhang, J., Lu, W., Peng, H., Xu, Z., Liu, X. (2018). Optimization in Cognitive Radio Networks with SWIPT-Based DF Relay. In: Meng, L., Zhang, Y. (eds) Machine Learning and Intelligent Communications. MLICOM 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 251. Springer, Cham. https://doi.org/10.1007/978-3-030-00557-3_16

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  • DOI: https://doi.org/10.1007/978-3-030-00557-3_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00556-6

  • Online ISBN: 978-3-030-00557-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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