TY - GEN
T1 - Energy-efficient task scheduling and resource allocation in downlink C-RAN
AU - Xia, Wenchao
AU - Zhang, Jun
AU - Quek, Tony Q.S.
AU - Jin, Shi
AU - Zhu, Hongbo
N1 - Funding Information:
†Jiangsu Key Laboratory of Wireless Communications, Nanjing University of Posts and Telecommunications, Nanjing 210003, P. R. China, Email: {2015010203, zhangjun, hbz}@njupt.edu.cn §Information Systems Technology and Design Pillar, Singapore University of Technology and Design, Singapore 487372, Singapore, Email: tonyquek@sutd.edu.sg ‡National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, P. R. China, Email: jinshi@seu.edu.cn This work of W. Xia, J. Zhang, and H. Zhu was supported by the National Natural Science Foundation of China (NSFC) under Grants 61427801 and 61671251, the Natural Science Foundation Program through Jiangsu Province of China under Grant BK20150852, and China Postdoctoral Science Foundation under Grants 2016M590481 and 2017T100391. The work of S. Jin was supported by NSFC for Distinguished Young Scholars under Grant 61625106 and NSFC under 61531011.
PY - 2018/6/8
Y1 - 2018/6/8
N2 - In this paper, we aim to minimize the network power consumption (NPC) in a downlink cloud radio access network. Not only the powers consumed at remote radio heads and fronthaul links for transmission, but also the power consumed at the baseband unit pool for computation is considered. We formulate a joint NPC minimization problem as a mixed timescale issue which can be regarded as a combination of two power minimization problems for computation and transmission, where the former is a slow timescale issue since task scheduling and computation resource allocation are usually executed in a large time space whereas the latter is a fast timescale issue due to the dependence on small-scale fading. To deal with timescale challenge, we introduce approximate results of the joint NPC minimization problem according to large system analysis and turn it into a slow timescale issue because the approximations are only dependent on statistical channel information. We propose an iterative coordinate descent algorithm based on branch-and-bound algorithm to find solutions to the joint NPC minimization problem. Numerical results show that the NPC decreases as the delay constraint increases but increases if the execution efficiency or computing capability of servers is degraded.
AB - In this paper, we aim to minimize the network power consumption (NPC) in a downlink cloud radio access network. Not only the powers consumed at remote radio heads and fronthaul links for transmission, but also the power consumed at the baseband unit pool for computation is considered. We formulate a joint NPC minimization problem as a mixed timescale issue which can be regarded as a combination of two power minimization problems for computation and transmission, where the former is a slow timescale issue since task scheduling and computation resource allocation are usually executed in a large time space whereas the latter is a fast timescale issue due to the dependence on small-scale fading. To deal with timescale challenge, we introduce approximate results of the joint NPC minimization problem according to large system analysis and turn it into a slow timescale issue because the approximations are only dependent on statistical channel information. We propose an iterative coordinate descent algorithm based on branch-and-bound algorithm to find solutions to the joint NPC minimization problem. Numerical results show that the NPC decreases as the delay constraint increases but increases if the execution efficiency or computing capability of servers is degraded.
UR - http://www.scopus.com/inward/record.url?scp=85049194696&partnerID=8YFLogxK
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U2 - 10.1109/WCNC.2018.8377118
DO - 10.1109/WCNC.2018.8377118
M3 - Conference contribution
AN - SCOPUS:85049194696
T3 - IEEE Wireless Communications and Networking Conference, WCNC
SP - 1
EP - 6
BT - 2018 IEEE Wireless Communications and Networking Conference, WCNC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE Wireless Communications and Networking Conference, WCNC 2018
Y2 - 15 April 2018 through 18 April 2018
ER -