Dynamic low earth orbit multi satellite hopping beam resource allocation considering load and dynamic coverage balance (LDCB-MSHBRA)

• Published in: Discover Space Vol. 128; no. 1; p. 3
• Main Authors: Li, Xin, Zhang, Xiaoning, Chang, Junde
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 16.09.2024; Springer Nature B.V
• Subjects: Astronomy; Astrophysics and Astroparticles; Earth motion; Earth orbits; Euler-Lagrange equation; Hopping (motion); Load balancing; Low earth orbit satellites; Low earth orbits; Objective function; Observations and Techniques; Optimization; Parameters; Physics; Physics and Astronomy; Planetology; Resource allocation; Resource utilization; Satellites; Space Exploration and Astronautics; Space Sciences (including Extraterrestrial Physics; Jumping beam; Low earth orbit satellite; Time slicing; Resource allocation; Dynamic low earth orbit
• ISSN: 0167-9295; 2948-295X; 1573-0794
• DOI: 10.1007/s11038-024-09557-5

A dynamic low earth orbit multi satellite hopping beam resource allocation method based on time slicing is proposed to address the issue of changing coverage and beam interference caused by satellite mobility in multi satellite and multi beam communication scenarios. The method involves six processes: (1) Establishing a low earth orbit satellite system with three identical configuration parameters and motion speed parameters; (2)Assign a value to the time slicing weight coefficient and use the principle of load balancing to minimize the difference in demand for dual star services as the optimization objective; (3) Obtain initial power resource allocation with maximum system capacity as the optimization objective; (4) Considering the mobility of low earth orbit satellites, updating weight coefficients and dynamically allocating power resources, a time resource dynamic allocation matrix and the optimal service cell set are obtained; (5) Update the independent coverage cell set of the third low earth orbit satellite, use the Lagrange equation of the weighted fair objective function to obtain the time resource allocation optimization matrix, and use one-way search to determine the optimal service cell set; (6) With the goal of maximizing system capacity, the optimal solution of the power resource allocation matrix for the third low earth orbit satellite is obtained. The system throughput is introduced to intuitively measure system performance, and adjustments are made based on the overlap of Samsung coverage. The resource allocation method is based on a fairness model, considering load balancing and dynamic coverage range changes. On the basis of improving the overall system throughput, it ensures the fairness of resource allocation and allocates time, frequency, and power resources to multiple satellites with overlapping coverage, which helps to improve the throughput and resource utilization of satellite systems.