TY - GEN
T1 - Exploring the interactions of communication, computing and caching in cloud RAN under two timescale
AU - Tang, Jianhua
AU - Teng, Long
AU - Quek, Tony Q.S.
AU - Chang, Tsung Hui
AU - Shim, Byonghyo
N1 - Funding Information:
This work was sponsored in part by NRF grant funded by the Korean Government (MSIP) (2016R1A2B3015576) and the Startup Funds of Chongquing University of Posts and Telecommunications (A2016-114)
Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/19
Y1 - 2017/12/19
N2 - 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 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. computational 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 affects the short-term beamforming in the remote radio heads. We formulate the problem as a stochastic mixed-integer nonlinear programming (SMINLP), and then approximate the problem as a global consensus problem. The alternating direction method of multipliers (ADMM) is utilized to obtain the solution in a distributed fashion. Simulation results demonstrate the that the proposed scheme is more cost saving than that without considering the integration of CC&C.
AB - 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 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. computational 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 affects the short-term beamforming in the remote radio heads. We formulate the problem as a stochastic mixed-integer nonlinear programming (SMINLP), and then approximate the problem as a global consensus problem. The alternating direction method of multipliers (ADMM) is utilized to obtain the solution in a distributed fashion. Simulation results demonstrate the that the proposed scheme is more cost saving than that without considering the integration of CC&C.
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U2 - 10.1109/SPAWC.2017.8227790
DO - 10.1109/SPAWC.2017.8227790
M3 - Conference contribution
AN - SCOPUS:85044229950
T3 - IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
SP - 1
EP - 6
BT - 18th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2017
Y2 - 3 July 2017 through 6 July 2017
ER -