FluidNet: A Flexible Cloud-Based Radio Access Network for Small Cells


Cloud-primarily based radio access networks (C-RAN) are proposed as a value-economical way of deploying tiny cells. Unlike conventional RANs, a C-RAN decouples the baseband processing unit (BBU) from the remote radio head (RRH), allowing for centralized operation of BBUs and scalable deployment of light-weight RRHs as small cells. During this work, we argue that the intelligent configuration of the front-haul network between the BBUs and RRHs, is essential in delivering the performance and energy advantages to the RAN and also the BBU pool, respectively. We propose FluidNet—a scalable, lightweight-weight framework for realizing the total potential of C-RAN. FluidNet deploys a logically re-configurable front-haul to use acceptable transmission methods in numerous components of the network and hence cater effectively to each heterogeneous user profiles and dynamic traffic load patterns. FluidNet's algorithms verify configurations that maximize the traffic demand happy on the RAN, while simultaneously optimizing the compute resource usage within the BBU pool. We prototype FluidNet on a half dozen BBU, half dozen RRH WiMAX C-RAN testbed. Prototype evaluations and large-scale simulations reveal that FluidNet's ability to re-configure its front-haul and tailor transmission ways provides a fiftyp.c improvement in satisfying traffic demands, while reducing the compute resource usage in the BBU pool by fiftypercent compared to baseline schemes.

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