FURI | Spring 2020
Improving Data Rate for 5G Systems using USRP Kits
In this research project, machine learning is utilized for channel estimation. Channel gains can be manually estimated, but the downside of manually calculating estimating the channels is that it is highly time-consuming. Therefore, in this project, machine learning algorithms are brought into play to reduce estimation time. The algorithms used throughout the project were designed in MATLAB and the resultant accuracy of the channel estimation was 40% and above.
Hometown: Tempe, Arizona, United States
Graduation date: Spring 2020