Beamforming for 5G Wireless Communication Systems using Machine Learning Methods, M.Sc. Thesis Sharif University of Technology ; Behroozi, Hamid (Supervisor) ; Fakharzadeh, Mohammad (Supervisor)
Abstract
The significant growth in wireless data traffic over the past few years has necessitated the use of new frequency bands for wireless communications. With the advent of the fifth-generation mobile network (5G), millimeter wave band will be widely employed for the purpose of wireless data transmission, increasing in channel bandwidth and data rate. Due to high propagation loss, severe vulnerability to blockage and poor reflection in millimeter wave frequencies, beamforming for antenna arrays is being considered a key enabler for millimeter wave applications in 5G. Beamforming contributes significantly to maintaining channel stability and capacity through enhancing Signal-to-Noise-Ratio (SNR)...
Cataloging briefBeamforming for 5G Wireless Communication Systems using Machine Learning Methods, M.Sc. Thesis Sharif University of Technology ; Behroozi, Hamid (Supervisor) ; Fakharzadeh, Mohammad (Supervisor)
Abstract
The significant growth in wireless data traffic over the past few years has necessitated the use of new frequency bands for wireless communications. With the advent of the fifth-generation mobile network (5G), millimeter wave band will be widely employed for the purpose of wireless data transmission, increasing in channel bandwidth and data rate. Due to high propagation loss, severe vulnerability to blockage and poor reflection in millimeter wave frequencies, beamforming for antenna arrays is being considered a key enabler for millimeter wave applications in 5G. Beamforming contributes significantly to maintaining channel stability and capacity through enhancing Signal-to-Noise-Ratio (SNR)...
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