Wireless Network Testbed for Network Slicing and Data-driven System Parameter Optimization
The goal of this project is to design and develop a wireless network testbed at the University of British Columbia (UBC) for Rogers Communications Canada Inc. to support different use cases for the fifth generation (5G) wireless networks. We will study the concept of self-organizing network (SON) and design a deep learning-based algorithm for our testbed to determine the optimal network parameters based on network traffic data and key performance indicator (KPI) statistics. We will also design a network traffic forecasting algorithm by capturing the mobility patterns of users. We will employ the proposed forecasting method to equip our testbed with mobility management algorithms for frequent handover operations. We will leverage SDN and network functions virtualization (NFV) to enable our testbed to support network slicing. We will design algorithms for dynamic radio resource allocation within each slice to satisfy the service requirements in each use case.