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Predicting Wireless MmWave Massive MIMO Channel Characteristics Using Machine Learning Algorithms
Joint Authors
Wang, Cheng-Xiang
Bai, Lu
Huang, Jie
Xu, Qian
Yang, Yuqian
Goussetis, George
Sun, Jian
Zhang, Wensheng
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-08-23
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Information Technology and Computer Science
Abstract EN
This paper proposes a procedure of predicting channel characteristics based on a well-known machine learning (ML) algorithm and convolutional neural network (CNN), for three-dimensional (3D) millimetre wave (mmWave) massive multiple-input multiple-output (MIMO) indoor channels.
The channel parameters, such as amplitude, delay, azimuth angle of departure (AAoD), elevation angle of departure (EAoD), azimuth angle of arrival (AAoA), and elevation angle of arrival (EAoA), are generated by a ray tracing software.
After the data preprocessing, we can obtain the channel statistical characteristics (including expectations and spreads of the above-mentioned parameters) to train the CNN.
The channel statistical characteristics of any subchannels in a specified indoor scenario can be predicted when the location information of the transmitter (Tx) antenna and receiver (Rx) antenna is input into the CNN trained by limited data.
The predicted channel statistical characteristics can well fit the real channel statistical characteristics.
The probability density functions (PDFs) of error square and root mean square errors (RMSEs) of channel statistical characteristics are also analyzed.
American Psychological Association (APA)
Bai, Lu& Wang, Cheng-Xiang& Huang, Jie& Xu, Qian& Yang, Yuqian& Goussetis, George…[et al.]. 2018. Predicting Wireless MmWave Massive MIMO Channel Characteristics Using Machine Learning Algorithms. Wireless Communications and Mobile Computing،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1216433
Modern Language Association (MLA)
Bai, Lu…[et al.]. Predicting Wireless MmWave Massive MIMO Channel Characteristics Using Machine Learning Algorithms. Wireless Communications and Mobile Computing No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1216433
American Medical Association (AMA)
Bai, Lu& Wang, Cheng-Xiang& Huang, Jie& Xu, Qian& Yang, Yuqian& Goussetis, George…[et al.]. Predicting Wireless MmWave Massive MIMO Channel Characteristics Using Machine Learning Algorithms. Wireless Communications and Mobile Computing. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1216433
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1216433