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- W4309965033 abstract "An 5G wireless network is studied to maximize the data rates between the base-station and mobile-station in an urban area. Antennas of the base-station and mobile-station are designed using a printed dipole element operating at 28 GHz. Machine Learning (ML) is applied for the optimization and improvement of the data rates. To build an accurate ML model DoE (Design of Experiments) based data collection algorithm is employed. A mathematical (regression) model is built and used for optimizing antenna orientations to maximize the data throughput." @default.
- W4309965033 created "2022-11-30" @default.
- W4309965033 creator A5019083787 @default.
- W4309965033 date "2022-10-09" @default.
- W4309965033 modified "2023-09-24" @default.
- W4309965033 title "5G Base-station Network Optimization in Urban Wireless Scenario using Machine Learning" @default.
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- W4309965033 doi "https://doi.org/10.23919/amta55213.2022.9954992" @default.
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