Description
In wireless communication systems, the process of data transmission includes the estimation of channels. Implementing machine learning in this process can reduce the amount of time it takes to estimate channels, thus, resulting in an increase of the system’s transmission throughput. This maximizes the performance of applications relating to device-to-device communications and 5G systems. However, applying machine learning algorithms to multi-base-station systems is not well understood in literature, which is the focus of this thesis.
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Details
Title
- Machine Learning for a Multi-Base-Station Cooperative 5G Cellular System
Contributors
- Cosio, Karla (Author)
- Ewaisha, Ahmed (Thesis director)
- Spanias, Andreas (Committee member)
- Barrett, The Honors College (Contributor)
- Electrical Engineering Program (Contributor)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2022-05
Resource Type
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