Python software tools for modeling telecommunication devices

Abstract

The study of the computer model of a telecommunications device modulator of a software-controlled network formed the prerequisites for the development and testing of software for such a device in order to optimize its functionality, performance, and reliability. At the same time, the necessary tools for the development of an efficient and flexible signal modulation device in software-controlled communication networks were identified. The main goal of the project was to create an effective computer model of the modulator that can adapt to changes in network conditions and ensure high quality data transmission. The test results showed that the model demonstrates high performance, stability in operation, and adaptability to various usage scenarios. The project sought to develop a model that not only works effectively at the current stage, but can also be easily adapted to future needs and technologies. Compatibility analysis and integration testing confirms that the model has a high degree of scalability and can be integrated with a variety of network components. Ensuring the resilience and reliability of the model was critical to ensure its effective operation in real-world conditions. The results of the robustness testing demonstrate that the model is able to operate stably for a long time, without loss of performance or errors. Several areas for optimization were identified, but overall the model meets the reliability requirements. The final goal of the project was to develop a model that can be easily integrated with existing telecommunication systems and software-defined networks. The results showed that the model is compatible with different operating systems and network equipment, which simplifies the process of its implementation and use in real projects. The computer model demonstrates high efficiency, adaptability, reliability, and ease of integration, meeting the needs of modern telecommunications systems. Nevertheless, the identified potential areas for further improvement indicate the need to continue working on the project, in particular, optimizing performance under high loads and expanding the model's functionality.