Joint Power Allocation and Beam Scheduling in Beam-Hopping Satellites: A Two-Stage Framework With a Probabilistic Perspective

Beam-hopping (BH) technology, integral to multi-beam satellite systems, adapts beam activation to the variable communication demands of terrestrial users. The optimization of power allocation and beam illumination scheduling constitutes the core design challenge in BH systems, especially under the c...

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Vydáno v:IEEE transactions on wireless communications Ročník 23; číslo 10; s. 14685 - 14701
Hlavní autoři: Chen, Lin, Wu, Linlong, Lagunas, Eva, Wang, Anyue, Lei, Lei, Chatzinotas, Symeon, Ottersten, Bjorn
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.10.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
beam hopping
binary quadratic programming
Design optimization
Energy consumption
Energy conversion efficiency
Energy minimization
Illumination
Iterative methods
Lighting
Payloads
power control
Quadratic programming
Resource management
Satellite broadcasting
Satellite communications
Satellites
Scheduling
Statistical analysis
Vectors
Wireless communication
Wireless communication
Satellites
beam hopping
Satellite broadcasting
Lighting
binary quadratic programming
Vectors
power control
Energy minimization
Resource management
Payloads
ISSN:1536-1276, 1558-2248, 1558-2248
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Popis
Shrnutí:Beam-hopping (BH) technology, integral to multi-beam satellite systems, adapts beam activation to the variable communication demands of terrestrial users. The optimization of power allocation and beam illumination scheduling constitutes the core design challenge in BH systems, especially under the constraint on a limited number of simultaneously active beams due to restricted radio frequency chain availability. This paper proposes a two-stage BH design solution, which minimizes energy consumption in BH satellite communications while accommodating the heterogeneous demands of users. The first stage addresses the coupling variables of power and beam status by recasting the allocation and scheduling problem through a statistical lens, thus breaking down the intricate relationship between variables. To manage the resulting non-convex challenge, we propose an iterative method that capitalizes on the optimality conditions inherent to this problem. This method is designed to procure a statistically-informed solution that aligns with our reformulated interpretation. Subsequently, the second stage maps this solution into a concrete beam illumination schedule, employing binary quadratic programming techniques. A penalty-based iterative method is applied, ensuring convergence to a locally optimal solution. Through numerical simulations, the proposed framework has been validated for its efficacy in improving energy efficiency and accurately matching demands.
Bibliografie:ObjectType-Article-1
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ISSN:1536-1276
1558-2248
1558-2248
DOI:10.1109/TWC.2024.3417707