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A Game Theory-Based Distributed Downlink Spectrum Sharing Method in Large-Scale Hybrid Satellite Constellations

2024/03/14 by Wei Li, Luliang Jia, Quan Chen +1 · 1 citation
Engineering · #Satellite Communication Systems #Advanced MIMO Systems Optimization #Advanced Wireless Network Optimization

paper · doi:10.1109/tcomm.2024.3375813

Abstract

Large-scale satellite constellations lead to a scarcity of spatial spectrum resources, especially for the overlapped spectrum between Low Earth Orbit ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LEO</i> ) and Geostationary Orbit ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">GEO</i> )satellites in hybrid constellations. Hence, based on game theory, a distributed spectrum-sharing method is proposed for downlink spectrum sharing in large-scale hybrid satellite constellations. Specifically, the system cycle is divided into equal-spaced topological periods, and the beams of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LEO</i> satellites are assigned to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LEO</i> ground stations ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LGS</i> ) during every topological period. A system model based on game theory is also developed to describe the mutual interference of links established between <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LEO</i> satellites and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LGS</i> . Subsequently, the formulated game is proven to be an exact potential game, with at least one pure strategic Nash equilibrium (NE). Along the line, to obtain the NE solution, a dynamic channel allocation algorithm is proposed based on stochastic learning theory, and the convergence is proven. Finally, the simulation results demonstrate the proposed DCASLA’s effectiveness, which can balance the convergence speed and overall network satisfaction.

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