Development of deep leaning algorithm for multiple-input multiple-output communication system
Multiple Input Multiple Output (MIMO) is the key technology of the fifth-generation (5G) communication technology. In order to meet the increasing communication needs of users, MIMO technology is also developing rapidly. MIMO signal detection plays a very important role in ensuring the accuracy of M...
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| 格式: | Final Year Project |
| 語言: | English |
| 出版: |
Nanyang Technological University
2022
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| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/158133 |
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| 機構: | Nanyang Technological University |
| 語言: | English |
| 總結: | Multiple Input Multiple Output (MIMO) is the key technology of the fifth-generation (5G) communication technology. In order to meet the increasing communication needs of users, MIMO technology is also developing rapidly. MIMO signal detection plays a very important role in ensuring the accuracy of MIMO signal transmission. In order to further improve the signal detection accuracy and efficiency of MIMO system, people try to design MIMO system detector by using machine learning.
This project will evaluate the performance of several conventional MIMO detection algorithms commonly used and several algorithms combined with machine learning. In this project, we will first introduce several commonly used detection algorithms, and theoretically analyze the advantages and problems of these methods. Then we make a comprehensive evaluation of each method through simulation experiment. Through our comprehensive analysis, the detection algorithm combining machine learning and iterative algorithm can effectively improve the efficiency and accuracy of signal detection. |
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