Method of integral estimation of channel state in the multiantenna radio communication systems
| Autor: | Oleksii Kuvshynov, Hryhorii Zubrytskyi, Ruslan Zhyvotovskyi, Andrii Shyshatskyi, Serhiy Gatsenko, Svitlana Kalantaievska, Sergii Petruk, Hennadii Pievtsov, Serhii Yarosh, Vitalii Zuiko |
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| Rok vydání: | 2018 |
| Předmět: |
Sequence
Frequency response Computational complexity theory Artificial neural network Computer science Applied Mathematics Mechanical Engineering Fuzzy set 0211 other engineering and technologies Energy Engineering and Power Technology 020206 networking & telecommunications 02 engineering and technology Communications system Industrial and Manufacturing Engineering Computer Science Applications Control and Systems Engineering Management of Technology and Innovation 021105 building & construction 0202 electrical engineering electronic engineering information engineering State (computer science) Electrical and Electronic Engineering Algorithm Computer Science::Information Theory Communication channel |
| Zdroj: | Eastern-European Journal of Enterprise Technologies. 5:60-76 |
| ISSN: | 1729-4061 1729-3774 |
| DOI: | 10.15587/1729-4061.2018.144085 |
| Popis: | A method of integrated estimation of channel state in multiantenna radio communication systems was developed. The distinguishing feature of the proposed method is estimation for several indicators, namely the bit error probability in the channel, frequency and pulse response of the channel state. After obtaining of the channel estimate for each indicator, a generalized channel state estimate is formed. Formation of the channel state estimate for each of the estimation indicators takes place in a separate layer of the neural network using the apparatus of fuzzy sets after which a generalized estimate is formed at the neural network output. Development of the proposed method was determined by necessity to raise speed of estimation of the channel state in multiantenna radio communication systems at an acceptable computational complexity. According to the results of the study, it has been established that the proposed method makes it possible to increase speed of estimation of channel state in multiantenna systems on average up to 30 % depending on the channel state while accuracy of the channel state estimation decreases by 5‒7 % because of reduced informativeness of estimation (because of using the apparatus of fuzzy sets) and is able to adapt to the signaling situation in the channel by training the neural network. Neural network training takes place on the basis of a training sequence and completes adaptation to the channel state after 10‒12 iterations of training. It is advisable to apply this method in radio stations with a programmable architecture to improve their interference immunity by reducing time for making decision on the channel state. |
| Databáze: | OpenAIRE |
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