IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i7p909-d103495.html
   My bibliography  Save this article

Optimal Power Allocation for a Relaying-Based Cognitive Radio Network in a Smart Grid

Author

Listed:
  • Kai Ma

    (School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China)

  • Xuemei Liu

    (School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China)

  • Jie Yang

    (School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
    Key Laboratory of System Control and Information Processing, Ministry of Education, Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China)

  • Zhixin Liu

    (School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China)

  • Yazhou Yuan

    (School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China)

Abstract

This paper obtains optimal power allocation to the data aggregator units (DAUs) and relays for cognitive wireless networks in a smart grid (SG). Firstly, the mutual interference between the primary user and the DAU are considered, and the expressions of the DAU transmission signal are derived based on the sensing information. Secondly, we use the particle swarm optimization (PSO) algorithm to search for the optimal power allocation to minimize the costs to the utility company. Finally, the impact of the sensing information on the network performance is studied. Then two special cases (namely, that only one relay is selected, and that the channel is not occupied by the primary user) are discussed. Simulation results demonstrate that the optimal power allocation and the sensing information of the relays can reduce the costs to the utility company for cognitive wireless networks in a smart grid.

Suggested Citation

  • Kai Ma & Xuemei Liu & Jie Yang & Zhixin Liu & Yazhou Yuan, 2017. "Optimal Power Allocation for a Relaying-Based Cognitive Radio Network in a Smart Grid," Energies, MDPI, vol. 10(7), pages 1-17, July.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:7:p:909-:d:103495
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/7/909/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/10/7/909/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xin Liu & Zhenyu Na & Min Jia & Xuemai Gu & Xiaotong Li, 2016. "Multislot Simultaneous Spectrum Sensing and Energy Harvesting in Cognitive Radio," Energies, MDPI, vol. 9(7), pages 1-13, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jen-Hao Teng & Chia-Wei Chao & Bin-Han Liu & Wei-Hao Huang & Jih-Ching Chiu, 2018. "Communication Performance Assessment for Advanced Metering Infrastructure," Energies, MDPI, vol. 12(1), pages 1-17, December.
    2. Kai Ma & Yege Bai & Jie Yang & Yangqing Yu & Qiuxia Yang, 2017. "Demand-Side Energy Management Based on Nonconvex Optimization in Smart Grid," Energies, MDPI, vol. 10(10), pages 1-17, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Enwei Xu & Shuo Shi & Dawei Chen & Xuemai Gu, 2018. "A joint optimization of energy harvesting and spectrum sensing for wireless sensor networks under Middleton Class A noise," International Journal of Distributed Sensor Networks, , vol. 14(5), pages 15501477187, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:10:y:2017:i:7:p:909-:d:103495. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.