ETRI Journal

Electronics and Telecommunications Research Institute (한국전자통신연구원)
권호 표지
DOI QR코드

DOI QR Code

Dynamic power and bandwidth allocation for DVB-based LEO satellite systems

  • Satya, Chan (IT Convergence Research Center, Division of Electronics Engineering, Jeonbuk National University) ;
  • Gyuseong, Jo (IT Convergence Research Center, Division of Electronics Engineering, Jeonbuk National University) ;
  • Sooyoung, Kim (IT Convergence Research Center, Division of Electronics Engineering, Jeonbuk National University) ;
  • Daesub, Oh (Radio and Satellite Research Division, ETRI) ;
  • Bon-Jun, Ku (Radio and Satellite Research Division, ETRI)
  • Received : 2022.05.19
  • Accepted : 2022.10.21
  • Published : 2022.12.10
Download PDF
⟨ Previous Next ⟩

Abstract

A low Earth orbit (LEO) satellite constellation could be used to provide network coverage for the entire globe. This study considers multi-beam frequency reuse in LEO satellite systems. In such a system, the channel is time-varying due to the fast movement of the satellite. This study proposes an efficient power and bandwidth allocation method that employs two linear machine learning algorithms and take channel conditions and traffic demand (TD) as input. With the aid of a simple linear system, the proposed scheme allows for the optimum allocation of resources under dynamic channel and TD conditions. Additionally, efficient projection schemes are added to the proposed method so that the provided capacity is best approximated to TD when TD exceeds the maximum allowable system capacity. The simulation results show that the proposed method outperforms existing methods.

Keywords

Acknowledgement

This research was supported by the Institute for Information and Communications Technology Promotion Grant funded by the Korea Government (MSIT, Development of the spectrum sharing technology for Non-GSO satellite system) under Grant 2021-0-00719.

References

  1. S. Xia, Q. Jiang, C. Zou, and G. Li, Beam coverage comparison of LEO satellite systems based on user diversification, IEEE Access 7 (2019), 181656-181667.
  2. S. Jung, G. Im, D. Jung, P. Kim, J. Ryu, and J. Kang, Performance analysis of DSSS- and CSS-based physical layer for IoT transmission over LEO satellites, ETRI J. 44 (2022), no. 4, 543-559. https://doi.org/10.4218/etrij.2021-0038
  3. X. Lin, S. Cioni, G. Charbit, N. Chuberre, S. Hellsten, and J. Boutillon, On the path to 6G: embracing the next wave of low earth orbit satellite access, IEEE Commun. Mag. 59 (2021), no. 12, 36-42.
  4. ETSI EN 302 307, Digital Video Broadcasting (DVB); Second generation framing structure, channel coding and modulation systems for Broadcasting, Interactive Services, News Gathering and other broadband satellite applications (DVB-S2), 2013.
  5. ETSI - EN 302 307-2 V1.2.1, Digital Video Broadcasting (DVB); Second generation framing structure, channel coding and modulation systems for Broadcasting, Interactive Services, News Gathering and other broadband satellite applications; Part 2: DVB-S2 Extensions (DVB-S2X), 2020.
  6. S. Chen, S. Sun, and S. Kang, System integration of terrestrial mobile communication and satellite communication-the trends, challenges and key technologies in B5G and 6G, China Commun. 17 (2020), no. 12, 156-171.
  7. S. Chan, H. Lee, S. Kim, and D. Oh, Intelligent low complexity resource allocation method for integrated satellite-terrestrial systems, IEEE Wirel. Commun. Lett. 11 (2022), no. 5, 1087-1091. https://doi.org/10.1109/LWC.2022.3157062
  8. M. Jia, X. Zhang, X. Gu, Q. Guo, Y. Li, and P. Lin, Interbeam interference constrained resource allocation for shared spectrum multibeam satellite communication systems, IEEE Int. Things J. 6 (2019), no. 4, 6052-6059. https://doi.org/10.1109/jiot.2018.2870878
  9. O. Kodheli, N. Maturo, S. Chatzinotas, S. Andrenacci, and F. Zimmer, NB-IoT via LEO satellites: an efficient resource allocation strategy for uplink data transmission, IEEE Int. Things J. 9 (2022), no. 7, 5094-5107. https://doi.org/10.1109/JIOT.2021.3109456
  10. U. Park, H. Kim, D. Oh, and B.-J. Ku, Interference-limited dynamic resource management for an integrated satellite-terrestrial system, ETRI J. 36 (2014), 519-527. https://doi.org/10.4218/etrij.14.0113.0079
  11. Q. Tang, Z. Fei, B. Li, and Z. Han, Computation offloading in LEO satellite networks with hybrid cloud and edge computing, IEEE Int. Things J. 8 (2021), no. 11, 9164-9176. https://doi.org/10.1109/JIOT.2021.3056569
  12. D. Zhou, M. Sheng, Y. Wang, J. Li, and Z. Han, Machine learning-based resource allocation in satellite networks supporting internet of remote things, IEEE Trans. Wirel. Commun. 20 (2021), no. 10, 6606-6621. https://doi.org/10.1109/TWC.2021.3075289
  13. R. Piziak and P. L. Odell, Affine projections, Comput. Math. Appl. 48 (2004), no. 1, 177-190. https://doi.org/10.1016/j.camwa.2004.07.001
  14. I. del Portillo Barrios, B. Cameron, and E. Crawley, A technical comparison of three low earth orbit satellite constellation systems to provide global broadband, Acta Astronautica 159 (2019), 123-135.  https://doi.org/10.1016/j.actaastro.2019.03.040