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Optimal Resource Allocation for Energy Harvesting Cognitive Radio Network with Q Learning

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Artificial Intelligence and Security (ICAIS 2019)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11632))

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Abstract

In order to improve the utilization of available resources in wireless networks, this paper studies the resource allocation problem of underlay cognitive wireless network based on energy harvesting (EH-CRN). Our goal is to maximize the capacity of the EH-CRN by allocation optimal power while considering interference, SINR, energy conservation, and quality of service (QoS) guarantees. A Q-learning EH resource allocation algorithm based on reinforcement learning (QLRA-EHCRN) is proposed to solve the non-convex nonlinear programming optimization problem. Theoretical analysis and simulation results show that the proposed algorithm can effectively improve the system capacity, reduce the average delay, and improve the resource utilization of EH-CRN.

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Acknowledgments

This work was partially supported by National Natural Science Foundation of China (No. 61771410), by Postgraduate Innovation Fund Project by Southwest University of Science and Technology (No. 18ycx115), by 2017, 2018 Artificial Intelligence Key Laboratory of Sichuan Province (No. 2017RYY05, No. 2018RYJ03), and by Horizontal Project (No. HX2017134, No. HX2018264).

Author information

Authors and Affiliations

  1. School of Information Engineering, South West University of Science and Technology, Mianyang, 621010, Sichuan, China

    Xiaoli He, Hong Jiang, Yu Song, Xiufeng Yang & He Xiao

  2. School of Computer Science, Sichuan University of Science and Engineering, Zigong, 643000, China

    Xiaoli He

  3. Department of Network Information Management Center, Sichuan University of Science and Engineering, Zigong, 643000, China

    Yu Song

Authors
  1. Xiaoli He
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  2. Hong Jiang
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  3. Yu Song
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  4. Xiufeng Yang
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  5. He Xiao
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Corresponding author

Correspondence to Xiaoli He .

Editor information

Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Zhaoqing Pan

  3. Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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He, X., Jiang, H., Song, Y., Yang, X., Xiao, H. (2019). Optimal Resource Allocation for Energy Harvesting Cognitive Radio Network with Q Learning. In: Sun, X., Pan, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2019. Lecture Notes in Computer Science(), vol 11632. Springer, Cham. https://doi.org/10.1007/978-3-030-24274-9_50

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  • DOI: https://doi.org/10.1007/978-3-030-24274-9_50

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-24273-2

  • Online ISBN: 978-3-030-24274-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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