On the Interactions of Communication, Computing and Caching in Cloud RAN under Two Timescales

  

 

There is a trend that the functionalities of communication, computing, and caching (CC&C) are merging together in the future networks. Recently, this mergence is formed by the concept of cloud radio access network (C-RAN) with caching as a service (CaaS). In this talk, we dissect the interactions of CC&C in C-RAN with CaaS from two dimensions: physical resource dimension and time dimension. In the physical resource dimension, we identify how to segment the baseband unit (BBU) pool resources (i.e. computation and storage) into different types of virtual machines (VMs). In the time dimension, we address how the long-term resource segmentation in the BBU pool impacts on the optimal short-time radio resource allocation (e.g., transmit beamforming design) at the remote radio heads. We formulate the problem as a stochastic mixed-integer nonlinear programming (SMINLP) to minimize the system cost. After a series of approximation, including sample average approximation, successive convex approximation, and semidefinite relaxation, the SMINLP is approximated as a global consensus problem. The alternating direction method of multipliers (ADMM) is utilized to obtain the solution in a distributed and parallel fashion. We also show the simulation results to confirm that the proposed scheme is more cost-saving than that without considering the integration of CC&C.