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An Energy-Efficient Dynamic Spectrum Access Approach for Internet of Things Applications

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Abstract

Energy efficiency has become the main problem of the communication network for sustainable development. The highly energy-efficient communication has become research focus and hotspot. Traditional network designs only consider network efficiency or network minimum energy consumption, but rarely consider maximum energy efficiency of networks. This paper presents an energy-efficient dynamic spectrum access approach for internet of things applications. We consider that communications between secondary users does not affect normal communications of primary users. The minimum interference problem between secondary users and primary users is discussed. By taking maximal energy efficiency as the optimal goal, we propose the energy efficient channel allocation strategy and sleeping mechanism. Then by minimizing the interference between secondary users and primary users, we can improve system throughput. The sleeping mechanism is utilized to minimize network energy consumption and establish the end-to-end cognitive multi-hop routing. Simulation results show that our algorithm is effective and feasible.

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Acknowledgments

This work was supported in part by the National Natural Science Foundation of China (No. 61571104), the Sichuan Science and Technology Program (No. 2018JY0539), the Key projects of the Sichuan Provincial Education Department (No. 18ZA0219), the Fundamental Research Funds for the Central Universities (No. ZYGX2017KYQD170), the CERNET Innovation Project (No. NGII20190111), the Fund Projects (Nos. 2020-JCJQ-ZD-016-11, 61403110405, 315075802, JZX6Y202001010161), and the Innovation Funding (No. 2018510007000134). The authors wish to thank the reviewers for their helpful comments.

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Correspondence to Dingde Jiang .

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Chen, J., Jiang, D., Yang, W., Fan, X. (2022). An Energy-Efficient Dynamic Spectrum Access Approach for Internet of Things Applications. In: Jiang, D., Song, H. (eds) Simulation Tools and Techniques. SIMUtools 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 424. Springer, Cham. https://doi.org/10.1007/978-3-030-97124-3_9

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  • DOI: https://doi.org/10.1007/978-3-030-97124-3_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-97123-6

  • Online ISBN: 978-3-030-97124-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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