Performance Analysis for Multi-hop Cognitive Radio Networks with Energy Harvesting by Using Stochastic Geometry

Ge, Lu; Chen, Gaojie; Zhang, Yue; Tang, Jie; Wang, Jintao; Chambers, Jonathon A

Performance Analysis for Multi-hop Cognitive Radio Networks with Energy Harvesting by Using Stochastic Geometry

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posted on 2020-04-02, 15:33 authored by Lu Ge, Gaojie Chen, Yue Zhang, Jie Tang, Jintao Wang, Jonathon A Chambers

- Cognitive multihop relaying has been widely considered for device-to-device (D2D) communications for applications in the physical layer of the Internet of Things. In this article, we construct a multihop cellular D2D communications system model with energy harvesting (EH) in underlay cognitive radio networks. The locations of primary user equipments (PUEs) and cellular base stations are considered as a Poisson point process in this model. The transmit power of secondary devices is collected from the power beacon with time-switching EH policy. Two charging policies for different applications are considered in this article. Then, the end-to-end outage probability analysis expressions of these two scenarios for the transmission scheme subject to interferences from PUEs are derived. The optimal harvesting time ratio is obtained to get the maximum capacity for end-to-end D2D communications. The analytical results are validated by performing the Monte Carlo simulation of the end-to-end outage probability, which is based on the half-duplex transmission scheme. The results of this article provide a potential pathway to reduce reliance on grid or battery energy supplies and, hence, further strengthen the benefits for the environment and deployment of future smart devices.

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Citation

IEEE Internet of Things Journal, 2020, Volume 7, Issue 2

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Department of Engineering

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AM (Accepted Manuscript)

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IEEE Internet of Things Journal

Volume

7

Issue

2

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

eissn

2327-4662

Copyright date

2019

Publisher DOI

https://doi.org/10.1109/JIOT.2019.2953130

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https://ieeexplore.ieee.org/abstract/document/8896898

Language

en

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Keywords

Amplify and forward communication Cellular radio Cognitive radio Cooperative communication Energy harvesting Monte Carlo methods Probability Radiofrequency interference Stochastic processes Telecommunication network reliability Telecommunication power management Cognitive networks Device-to-device (D2D)Internet of Things (IoT)Multihop Outage probability Stochastic geometry

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Performance Analysis for Multi-hop Cognitive Radio Networks with Energy Harvesting by Using Stochastic Geometry

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