This paper describes a wireless communication model based on IEEE 802.11n. Typical methods for channel equalisation and estimation are described, such as the least squares method and the minimum mean square error method. Equalization based on deep learning was used as well. Coded and uncoded bit error rate was used as a performance identifier. Experiments with topology of the neural network has been performed. Programming languages such as MATLAB and Python were used in this work.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:400540 |
| Date | January 2019 |
| Creators | Hubík, Daniel |
| Contributors | Staněk, Miroslav, Miloš, Jiří |
| Publisher | Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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