学术讲座 | 双时间尺度下的云无线接入网之通信，计算和缓存的交互

讲座题目：双时间尺度下的云无线接入网之通信，计算和缓存的交互

时间&日期：2017年10月26日，16点至17点

地点：Teaching A 202

主讲人：唐建华 教授 （国立首尔大学）

摘要：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-term 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.

关于演讲人： Jianhua Tang received the B.E. degree in Communications Engineering from Northeastern University, China, in 2010, and the Ph.D. degree in Electrical and Electronic Engineering from Nanyang Technological University, Singapore, in 2015. He was a Post-Doctoral Research Fellow with the Singapore University of Technology and Design from 2015 to 2016. He is currently a Research Assistant Professor with the Department of Electrical and Computer Engineering, Seoul National University, Korea. His research interests include cloud computing, content-centric network, and cloud radio access network.