Cloud-RAN Modeling Based on Parallel Processing

We consider in this paper the implementation of a cloud radio access network (C-RAN) on a centralized multicore system supporting the base band processing of several distributed antennas. We present a parallel processing model based on both functional and data decomposition of virtualized base band unit (BBU) functions in order to reduce their runtime. We study two scheduling strategies of parallel runnable BBU jobs, where computing resources can be allocated either per user equipments or else per code blocks. By using data obtained when running an open source RAN code (namely, OAI), we introduce a batch queuing model (the M
^{[X ]}
/M/C multi-service system) to assess the needed processing capacity in a data center while meeting tight latency requirements in the down-link and up-link directions. The proposed model is validated by simulation when processing a hundred LTE-cells in a multi-core system. Results provide valuable guidelines for sizing and deploying Cloud-RAN systems.