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Fast Beam Placement for Ultra-Dense LEO Networks

Trinh Van Chien, Nguyen Minh Quan, Tri Nhu Do, Cuong Le, Tan N. Nguyen, Symeon Chatzinotas

TL;DR

This letter formulates and solves a fast beam placement optimization problem for ultra-dense satellite systems to enhance the link budget with a minimum number of active beams (NABs) and proposes two algorithms for large user groups exploiting the modified K-means clustering and the graph theory.

Abstract

Low Earth orbit (LEO) satellites has brought about significant improvements in wireless communications, characterized by low latency and reduced transmission loss compared to geostationary orbit (GSO) satellites. Ultra-dense LEO satellites can serve many users by generating active beams effective to their locations. The beam placement problem is challenging but important for efficiently allocating resources with a large number of users. This paper formulates and solves a fast beam placement optimization problem for ultra-dense satellite systems to enhance the link budget with a minimum number of active beams (NABs). To achieve this goal and balance load among beams within polynomial time, we propose two algorithms for large user groups exploiting the modified K-means clustering and the graph theory. Numerical results illustrate the effectiveness of the proposals in terms of the statistical channel gain-to-noise ratio and computation time over state-of-the-art benchmarks.

Fast Beam Placement for Ultra-Dense LEO Networks

TL;DR

This letter formulates and solves a fast beam placement optimization problem for ultra-dense satellite systems to enhance the link budget with a minimum number of active beams (NABs) and proposes two algorithms for large user groups exploiting the modified K-means clustering and the graph theory.

Abstract

Low Earth orbit (LEO) satellites has brought about significant improvements in wireless communications, characterized by low latency and reduced transmission loss compared to geostationary orbit (GSO) satellites. Ultra-dense LEO satellites can serve many users by generating active beams effective to their locations. The beam placement problem is challenging but important for efficiently allocating resources with a large number of users. This paper formulates and solves a fast beam placement optimization problem for ultra-dense satellite systems to enhance the link budget with a minimum number of active beams (NABs). To achieve this goal and balance load among beams within polynomial time, we propose two algorithms for large user groups exploiting the modified K-means clustering and the graph theory. Numerical results illustrate the effectiveness of the proposals in terms of the statistical channel gain-to-noise ratio and computation time over state-of-the-art benchmarks.

Paper Structure

This paper contains 9 sections, 2 theorems, 7 equations, 9 figures, 2 algorithms.

Key Result

Lemma 1

Phase 2 of Algorithm pseudo:tgbp converges after $BK$ movements, with the NABs ($B$) and the number of users ($K$).

Figures (9)

  • Figure 1: Illustration of the system model, where multiple users can be served by the same beams.
  • Figure 2:
  • Figure 3:
  • Figure 4:
  • Figure 5:
  • ...and 4 more figures

Theorems & Definitions (4)

  • Lemma 1
  • proof
  • Lemma 2
  • proof