JOURNAL ARTICLE

Satellite constellation design for 5G wireless networks of mobile communications.

  • Published In: International Journal of Satellite Communications & Networking, 2023, v. 41, n. 5. P. 441 1 of 3

  • Database: Applied Science & Technology Source Ultimate 2 of 3

  • Authored By: Muttiah, Ravandran 3 of 3

Abstract

Summary: Satellite constellation design plays an important role in satellite networks. Network constellation system design can affect the effectiveness of current improvements of the communications link and the management of the entire network. The power requirement of the mobile stations and ground stations is very high in a geostationary Earth orbit communication system, which means the terrestrial terminal is hard to be made handheld for fifth generation mobile communications. The emergence of nongeostationary orbit satellites such as low Earth orbit satellites greatly compensates for the disadvantage of geostationary Earth orbit satellites. Based on the classical constellation design method, the orthogonal circular orbit constellation is proposed. The design objectives considered here are the following: global Earth coverage by low Earth orbit satellites, the duration of continuously covering one mobile station by one satellite is more than 9.57 min, the access satellite link duration time of the mobile station is more than 4.79 min, and the number of satellites and orbits is to be minimum. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Satellite Communications & Networking. 2023/09, Vol. 41, Issue 5, p441
  • Document Type:Article
  • Subject Area:Engineering
  • Publication Date:2023
  • ISSN:15420973
  • DOI:10.1002/sat.1477
  • Accession Number:169851354
  • Copyright Statement:Copyright of International Journal of Satellite Communications & Networking is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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