Machine Learning Application on 5G

Enhanced 5G performance by Stochastic Gradient Descent to allocate optimal data rates resource dynamically
Developed the efficient millimeter wave beams and power allocation, and users grouping system

Introduction


  • The increased rate demand in the upcoming 5G wireless systems and the fact that the spectral efficiency of microwave links is approaching its fundamental limits have motivated consideration of higher frequency bands that offer abundance of communication bandwidth.
  • Different solutions. Cloud computing, Femtocell, Millimeter wave, etc.
  • There is a growing consensus in both industry and academia that millimeter wave (mmWave) will play an important role in 5G wireless systems in providing very high data rates
  • Resource Allocation and Interference Management: The directional pencil- beam operation provides many options to form different cells and allocate resources, while significantly simplifying interference management. We identify new trade-offs among throughput enhancement, fair scheduling, and formulate a suitable optimization problem based on long-term resource allocation. Finally, we use directional beams at the BSs and/or the UEs.



Member


Sean Chung
sean.chung@wisc.edu
Justin Yang
justinyang00712@gmail.com