Abstract

Satellite communication system holds a crucial role in modern society, so it is significant to improve its reliability and stability. Optimizing reliability and designing redundancy become imperative methods to ensure continuous and efficient operation of the system in the intricate space environment. In this paper, we initially model the satellite communication system using a Markov Bayesian Network in conjunction with a non-working reserve system, facilitating a systematic analysis of its reliability. Secondly, we propose a novel Bayesian environmental importance measure by considering the unique attributes of the space environment. This importance measure verifies the contributions and significance of the individual subsystems within the satellite communication system. Subsequently, we formulate a redundancy design strategy for critical subsystems to maximize reliability while minimizing costs. To solve the optimal number of redundancies of components in the subsystem, we employ the multi-objective particle swarm optimization algorithm. Finally, the effectiveness of the proposed method is demonstrated by a satellite communication system.

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