Registration Number
2117U009373, Article
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Тези
Title
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Semenov A. O.
Semenova O. O.
Voznyak O.
Mostoviy D.
Dudatyev I.
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26-02-2017
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Вінницький національний технічний університет
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http://ir.lib.vntu.edu.ua/handle/123456789/14415
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Томская группа и студенческое отделение Института инженеров по электротехнике и радиоэлектронике ; Сибирский федеральный университет
Description
WiMAX is a broadband wireless last mile technology providing high speeds for long distances and offering great flexibility. Scheduling in WiMAX became one of the most important tasks, because it is responsible for distributing available resources among users. A high level of quality of service and scheduling support is one of the most interesting features of the WiMAX standard. In modern telecommunication networks the access control techniques are widely used. That is because using such devices instead of traditional ones permits to increase accuracy and reliability of control. Fuzzy systems have replaced conventional techniques in many engineering applications, especially in control systems. In the article it is suggested to use a fuzzy controller for access control in WiMAX networks that allows avoiding congestion in networks. The main objective of this work is providing an implementation of the WiMAX standard using the dynamic fuzzy logic based priority scheduler. We propose to use a fuzzy controller having three input and one output linguistic variables. Input linguistic variables of the controller are waiting time, queue length and packet size, its output variable is priority. A block diagram of the fuzzy controller was developed. Linguistic variables, terms and membership functions for input and output values have been defined. The Waiting time linguistic variable has three terms: low, medium, high. The Queue length linguistic variable has three terms: short, medium, long. The Packet size linguistic variable has three terms: small, medium, large. The rules base consisting of twenty-seven rules has been developed. The fuzzy controller has been simulated using Matlab 6.5. Results of the simulation prove the accuracy and reliability of the fuzzycontroller’s model.
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2026-10-26
