Olena Semenova

The UHF oscillators based on a HEMT structure with negative conductivity

The article considers a possibility of constructing microwave oscillators on a transistor structure with negative conductivity based on two HEMT. Obtained non-linear equations can be used to model microwave oscillator parameters and characteristics with an error not more than 10%.

Access fuzzy controller for CDMA networks

It is suggested to use a fuzzy-neural controller for access control in CDMA networks that allows avoiding congestion in networks. The fuzzy-controller for controlling users access has been designed. Linguistic variables, terms and membership functions for input and output values have been defined. A rule base has been developed.

Routing in telecommunication networks using fuzzy logic

In the paper it has been proposed to use a fuzzy-controller in telecommunication networks for improving the routing process. An architecture of the fuzzy-controller was developed. Linguistic variables, terms and membership functions for input and output values have been defined. Rules base has been developed. The operation of the fuzzy-controller has been simulated.

Genetic ANFIS for scheduling in telecommunication networks

The paper proposes using a fuzzy controller in telecommunication networks for improving the scheduling process. A structure of the fuzzy controller was developed. Linguistic variables, terms and membership functions for input and output values were defined. A rules base was developed. An Adaptive Neuro-fuzzy Inference System (ANFIS) on the base of the fuzzy-controller was developed. A genetic algorithm to improve the rule base was proposed. The operation of ANFIS was simulated and trained.

A Hybrid Approach to Call Admission Control in 5G Networks

Artificial intelligence is employed for solving complex scientific, technical, and practical problems. Such artificial intelligence techniques as neural networks, fuzzy systems, and genetic and evolutionary algorithms are widely used for communication systems management, optimization, and prediction. Artificial intelligence approach provides optimized results in a challenging task of call admission control, handover, routing, and traffic prediction in cellular networks. 5G mobile communications are designed as heterogeneous networks, whose important requirement is accommodating great numbers of users and the quality of service satisfaction. Call admission control plays a significant role in providing the desired quality of service. An effective call admission control algorithm is needed for optimizing the cellular network system. Many call admission control schemes have been proposed. The paper proposes a methodology for developing a genetic neurofuzzy controller for call admission in 5G networks. Performance of the proposed admission control is evaluated through computer simulation.

The neuro-fuzzy controller for handover operation in mobile networks

The paper proposes using a neuro-fuzzy controller in mobile networks for improving the handover process. An architecture of the neuro-fuzzy controller was developed. Linguistic variables, terms and membership functions for input and output values were defined. A rules base was developed. The operation of the neuro-fuzzy controller was simulated and trained.

The fuzzy neural networks with ternary encoding

When combining fuzzy logic and neural networks it is possible to get a hybrid system that can process uncertain values and can be trained. Fuzzy logic elements can be regarded as fuzzy-neural networks. In order to present a set of fuzzy values the ternary encoding is used. Three fuzzy neural networks on linear neurons are proposed. The first operates as a fuzzy logical minimum element, the second does as a fuzzy logical maximum element, the third - as a fuzzy logical complement element.