A new model for indoor propagation prediction using genetic algorithm

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Date

2008

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Publisher

Ieice-inst Electronics information Communications Eng

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Department of Electrical & Electronics Engineering
Department of Electrical and Electronics Engineering (EE) offers solid graduate education and research program. Our Department is known for its student-centered and practice-oriented education. We are devoted to provide an exceptional educational experience to our students and prepare them for the highest personal and professional accomplishments. The advanced teaching and research laboratories are designed to educate the future workforce and meet the challenges of current technologies. The faculty's research activities are high voltage, electrical machinery, power systems, signal and image processing and photonics. Our students have exciting opportunities to participate in our department's research projects as well as in various activities sponsored by TUBİTAK, and other professional societies. European Remote Radio Laboratory project, which provides internet-access to our laboratories, has been accomplished under the leadership of our department with contributions from several European institutions.

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Abstract

In this study, a new, simple and accurate computation of the received signal strength (RSS) level for indoor environment is performed. The genetic algorithm (GA) approach is used for prediction of the RSS. The proposed model is formed on the knowledge of measurements without requiring any detail of the environment. The model provides a time efficient method to estimate RSS dynamically at any location in the test environment. The accuracy of the measurement results and the genetic algorithm approach are presented for three distinct transmitters located at different positions.

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Keywords

indoor radio communication, propagation, genetic algorithm

Turkish CoHE Thesis Center URL

Citation

0

WoS Q

Q4

Scopus Q

Q4

Source

Volume

5

Issue

24

Start Page

1067

End Page

1073

URI

https://doi.org/10.1587/elex.5.1067
 https://hdl.handle.net/20.500.14411/1007

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