期刊
IEEE TRANSACTIONS ON COMMUNICATIONS
卷 67, 期 11, 页码 7755-7770出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCOMM.2019.2934854
关键词
C-RAN; caching as a service; two timescales; semidefinite relaxation (SDR); alternating direction method of multipliers (ADMM)
资金
- Korea Research Fellowship Program through the National Research Foundation of Korea (NRF) - Ministry of Science and ICT [2016H1D3A1938245]
- Hunan Provincial Science & Technology Project Foundation [2018TP1018, 2018RS3065]
- SUTD-ZJU Research Collaboration [SUTD-ZJU/RES/01/2016, SUTDZJU/RES/05/2016]
- NSFC, China [61571385, 61731018]
- Shenzhen Fundamental Research Fund [ZDSYS201707251409055, KQTD2015033114415450]
- MSIT, Korea, under the ITRC support program [IITP-20192017-0-01637]
- Samsung Research Funding & Incubation Center for Future Technology of Samsung Electronics [SRFC-IT1901-17]
- National Research Foundation of Korea [2016H1D3A1938245] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
Recently, cloud radio access network (C-RAN) with caching as a service (CaaS) was proposed to merge the functionalities of communication, computing, and caching (CC&C) together. In this paper, 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 short-term transmit beamforming at the remote radio heads. We formulate the problem as a stochastic mixed-integer nonlinear programming (SMINLP) to minimize the system cost, including the server cost, VM cost and wireless transmission 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 parallel fashion. Simulation results verify the convergence of our proposed algorithm, and also confirm that the proposed scheme is more cost-saving than that without considering the integration of CC&C.
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