Paper
6 November 2019 Applying artificial intelligence for cellular networks optimization
Author Affiliations +
Proceedings Volume 11176, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2019; 111761Z (2019) https://doi.org/10.1117/12.2536857
Event: Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2019, 2019, Wilga, Poland
Abstract
Artificial Intelligence may be used to solve complex technical and practical problems. Moreover, such Artificial Intelligence techniques as Fuzzy Systems, Artificial Neural Networks, Evolutionary and Genetic Algorithms have a great potential in providing optimization, prediction and management of communication system in a dynamic wireless environment. Artificial Intelligence approach provides optimized results in a challenging task of the call admission control process in cellular networks. The paper proposes a methodology for developing a genetic neuro-fuzzy controller for call admission in cellular networks. A structure of the access fuzzy controller was suggested. Linguistic variables, their terms as well as membership functions for input and output values were determined. A rule base was proposed. A Neuro-fuzzy System on the base of the fuzzy-controller was designed and simulated. A genetic algorithm was proposed for optimizing the rule base.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Olena O. Semenova, Andriy O. Semenov, Oleg V. Bisikalo, Volodymyr Yu. Kucheruk, Pavel I. Kulakov, Ryszard Romaniuk, Paweł Komada, and Karlygash Nurseitova "Applying artificial intelligence for cellular networks optimization", Proc. SPIE 11176, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2019, 111761Z (6 November 2019); https://doi.org/10.1117/12.2536857
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KEYWORDS
Fuzzy logic

Artificial intelligence

Samarium

Genetic algorithms

Networks

Device simulation

Fuzzy systems

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