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Flexible functional split in Cloud Radio Access Network (CRAN) greatly overcomes fronthaul capacity and latency challenges. In such architecture, part of the baseband processing is done locally and the remaining is done remotely in the central cloud. On the other hand, Energy Harvesting (EH) technologies are increasingly adopted due to sustainability and economic advantages. Power consumption due to baseband processing has a huge share in the total power consumption breakdown of smaller base stations. Given that such base stations are powered by EH, in addition to QoS constraints, energy availability also conditions the decision on where to place each baseband function in the system. This work focuses on determining the performance bounds of an optimal placement of baseband functional split option in virtualized small cells that are solely powered by EH. The work applies Dynamic Programming (DP), in particular, Shortest Path search is used to determine the optimal functional split option considering traffic requirements and available energy budget.
grant TEC2017-88373-R (5G-REFINE)
Networking and Internet Architecture (cs.NI), Signal Processing (eess.SP), FOS: Computer and information sciences, energy harvesting, dynamic programming, flexible functional split, Computer Science - Networking and Internet Architecture, SDN, NFV, virtual base stations, CRAN, FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Signal Processing
Networking and Internet Architecture (cs.NI), Signal Processing (eess.SP), FOS: Computer and information sciences, energy harvesting, dynamic programming, flexible functional split, Computer Science - Networking and Internet Architecture, SDN, NFV, virtual base stations, CRAN, FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Signal Processing
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