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<p>Cohesive clustered satellites have better scalability, spatial diversity, and coverage maintainability compared with conventional single satellite platforms. However, the high complexity of massive self-organizing satellites and malicious jamming of wireless channels pose severe threats to cohesive clustered satellite systems. By utilizing game-theoretic clustering to dynamically adjust the topology of cohesive clustered satellites, combined with the use of the reconfigurable intelligent surface (RIS) for reconfiguring the jamming environment, a multi-RIS-assisted cohesive clustered satellite anti-jamming system was developed for achieving reliable communication in the presence of malicious jamming. Specifically, game-theoretic clustering forms multiple coalitions for cohesive satellites, after which the satellite RIS can constructively enhance the desired signals while destructively weakening the jamming signals within one coalition. Building upon the above system, the aim of this study is to maximize the sum rate by jointly optimizing the satellite clustering, transceiver beamforming, and phase shifts of the satellite RIS when the jammer’s channel state information (CSI) is imperfect. To solve the intractable problem, the satellite clustering was first optimized by formulating a coalition formation game, where a partial optimal coalition preference order was proposed for maximizing the sum rate. Subsequently, after converting the jammer’s imperfect CSI into a robust CSI by adopting the discretization method, an alternative optimization method was developed for designing the transceiver beamforming and determining the phase shifts of the satellite RIS by leveraging the zero-forcing precoder, cyclic coordinate descent optimization framework, and linear minimum-mean-square-error decoder. The results prove that the proposed game-theoretic clustering method can converge to stable coalition formation with the exact potential game. The numerical simulation results demonstrate the superiority and validity of the proposed schemes compared to existing benchmark schemes.</p>

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Game-theoretic clustering and scalable beamforming for multi-RIS-assisted cohesive satellite anti-jamming systems

  • 期刊论文

  • 发表日期：

    2025年8月15日

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  • Yucong Cao,
  • Yifu Sun,
  • Yonggang Zhu,
  • Kang An,
  • Zhi Lin

摘要

Cohesive clustered satellites have better scalability, spatial diversity, and coverage maintainability compared with conventional single satellite platforms. However, the high complexity of massive self-organizing satellites and malicious jamming of wireless channels pose severe threats to cohesive clustered satellite systems. By utilizing game-theoretic clustering to dynamically adjust the topology of cohesive clustered satellites, combined with the use of the reconfigurable intelligent surface (RIS) for reconfiguring the jamming environment, a multi-RIS-assisted cohesive clustered satellite anti-jamming system was developed for achieving reliable communication in the presence of malicious jamming. Specifically, game-theoretic clustering forms multiple coalitions for cohesive satellites, after which the satellite RIS can constructively enhance the desired signals while destructively weakening the jamming signals within one coalition. Building upon the above system, the aim of this study is to maximize the sum rate by jointly optimizing the satellite clustering, transceiver beamforming, and phase shifts of the satellite RIS when the jammer’s channel state information (CSI) is imperfect. To solve the intractable problem, the satellite clustering was first optimized by formulating a coalition formation game, where a partial optimal coalition preference order was proposed for maximizing the sum rate. Subsequently, after converting the jammer’s imperfect CSI into a robust CSI by adopting the discretization method, an alternative optimization method was developed for designing the transceiver beamforming and determining the phase shifts of the satellite RIS by leveraging the zero-forcing precoder, cyclic coordinate descent optimization framework, and linear minimum-mean-square-error decoder. The results prove that the proposed game-theoretic clustering method can converge to stable coalition formation with the exact potential game. The numerical simulation results demonstrate the superiority and validity of the proposed schemes compared to existing benchmark schemes.