| Faced with the problems like serious jamming, increasingly complex electromagnetic environment and the difficulty of ensuring the reliability in the wireless communication system, search for strong anti-jamming measures becomes important subjects. This paper presents dynamic anti-jamming decision-making methods, which make decisions on multi-domain parameters of the system like power, frequency, modulation and coding domain based on jamming cognition, by this way, enhancing the system’s adaptability to the jamming environment and reducing the spectrum and power cost.First, this paper introduces the model about the one-way link of the system and the working environment of the decision-making module. Then designs an anti-jamming decision-making engine based on the rough set theory as well as provides the decision criterions and constraints. And then focuses on reducing the compressed decision-making space based on the rough set theory to obtain universal decision-making rules, which concludes reducing the condition attributes and their values. Theoretical analysis and simulation prove the engine’s ability.Second, design an engine based on the concept of combining the decision rules with the traditional GA, we use the rules to screen the initial population generated by GA randomly. According to the practical application, we present an objective function which is independent of weights. Simulation proves the improved algorithm could improve GA’s convergence rate with the same accuracy.Last, design an engine based on the concept of combining the decision rules with the cases. To be more objective, we present a kind of weight calculation method which doesn’t rely on experiences. To solve the problem of case reuse, we put forward a kind of multiple feature matching algorithm based on features’ importance, which realizes the integration of multi experiences. The RBR technique completes the CBR system. Theoretical analysis and simulation prove the engine’s ability. |
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