IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i15p1718-d598668.html
   My bibliography  Save this article

Strategy of Multi-Beam Spot Allocation for GEO Data Relay Satellite Based on Modified K-Means Algorithm

Author

Listed:
  • Huiliang Liu

    (Institute of Telecommunication and Navigation Satellites, China Academy of Space Technology, Beijing 100094, China
    Innovation Center of Satellite Communication System, China National Space Administration, Beijing 100094, China)

  • Yao Chu

    (Department of Precision Instrument, Tsinghua University, Beijing 100084, China)

  • Yulong Zhang

    (School of Integrated Circuits, Tsinghua University, Beijing 100084, China)

  • Weiguo Hou

    (Institute of Telecommunication and Navigation Satellites, China Academy of Space Technology, Beijing 100094, China
    Innovation Center of Satellite Communication System, China National Space Administration, Beijing 100094, China)

  • Yinqiao Li

    (Institute of Telecommunication and Navigation Satellites, China Academy of Space Technology, Beijing 100094, China
    Innovation Center of Satellite Communication System, China National Space Administration, Beijing 100094, China)

  • Yuan Yao

    (Institute of Telecommunication and Navigation Satellites, China Academy of Space Technology, Beijing 100094, China
    Innovation Center of Satellite Communication System, China National Space Administration, Beijing 100094, China)

  • Yaxing Cai

    (Institute of Telecommunication and Navigation Satellites, China Academy of Space Technology, Beijing 100094, China
    Innovation Center of Satellite Communication System, China National Space Administration, Beijing 100094, China)

Abstract

With the booming development of satellite applications, the giant constellations of low Earth orbit (LEO) satellites have introduced challenges for the data relay service. The multi-beam satellite not only offers concurrent access to a large number of objects, but can also meet the high data requirements toward specific coverage of the LEO constellation. However, the multi-beam satellite often faces the mismatch problem of spot allocation and data requirements, which can cause an overload traffic jam or a waste of resources. An optimization algorithm on spot beam allocation is necessary to automatically place the spot centers with appropriate beam widths in line with the density of the traffic demands and to realize the uniformity of the beam occupation. Compared with the conventional K-means algorithm, two adjustable parameters α and β are introduced: one for tuning the ratio of two components making up the distance matrix, and the other for setting the obligatory minimum number of objects per beam. In this paper, the whole process of the proposed method is demonstrated, including the establishment of the low-orbit satellite constellation model, the extraction of the distribution features, and the implementation and evaluation of the modified K-means algorithm. The results prove the validity of the proposed algorithm. A larger value of β with a relative smaller value of α tends to obtain the uniformity of beam occupation; the minimum standard deviation of objects per beam is achieved when α is 0.2 and β is 0.8. This demonstrates that the uniformity of objects per beam can be realized by adjusting the parameters of the distance determination matrix and the obligatory minimal number of objects in each beam. The impact of parameter range on the results is also analyzed.

Suggested Citation

  • Huiliang Liu & Yao Chu & Yulong Zhang & Weiguo Hou & Yinqiao Li & Yuan Yao & Yaxing Cai, 2021. "Strategy of Multi-Beam Spot Allocation for GEO Data Relay Satellite Based on Modified K-Means Algorithm," Mathematics, MDPI, vol. 9(15), pages 1-16, July.
  • Handle: RePEc:gam:jmathe:v:9:y:2021:i:15:p:1718-:d:598668
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/15/1718/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/9/15/1718/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jean-Thomas Camino & Christian Artigues & Laurent Houssin & Stéphane Mourgues, 2019. "Linearization of Euclidean norm dependent inequalities applied to multibeam satellites design," Computational Optimization and Applications, Springer, vol. 73(2), pages 679-705, June.
    Full references (including those not matched with items on IDEAS)

    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. Aloïs Duguet & Christian Artigues & Laurent Houssin & Sandra Ulrich Ngueveu, 2022. "Properties, Extensions and Application of Piecewise Linearization for Euclidean Norm Optimization in $$\mathbb {R}^2$$ R 2," Journal of Optimization Theory and Applications, Springer, vol. 195(2), pages 418-448, November.

    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:jmathe:v:9:y:2021:i:15:p:1718-:d:598668. 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.