The relevance of the study was determined by the need to improve the reliability of communication in Flying Ad Hoc Networks, where traditional routing protocols do not take into account channel quality and rapid topology changes. The aim of the work was to develop an intelligent decision-making system capable of adaptively selecting a data transmission route according to the state of the radio channel. To achieve this aim, methods of fuzzy logic, mathematical modelling, simulation experiments and comparative analysis of routing efficiency were used. During the study, a model of a fuzzy expert system was created that evaluates the quality of communication based on the signal-to-noise ratio, the distance between nodes, and noise indicators, forms a database of IF-THEN rules, and determines the optimal transmission path – direct or via a repeater. Experimental results showed that the proposed system increases the Packet Delivery Ratio to 99%, while in the basic algorithms it was only 90%. The average transmission delay decreased from 80 to 50 ms, and the number of connection interruptions decreased from 0.2 to 0 cases per min. It was also found that the system maintains network stability under conditions of signal-to-noise ratio fluctuations, ensuring smooth route switching without excessive protocol traffic. The use of fuzzy logic made it possible to take into account the uncertainty of the radio environment and proactively respond to signal quality degradation, preventing connection drops. The practical value of the work lies in the possibility of integrating the developed system into drone network modules to ensure reliable routing in highly mobile conditions, particularly in military, search and rescue, and civil applications
Zaivyi et al. (Wed,) studied this question.