TY - JOUR
T1 - Power minimization-based joint 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:
Manuscript received October 4, 2017; revised March 22, 2018 and June 20, 2018; accepted August 9, 2018. Date of publication August 24, 2018; date of current version November 9, 2018. The work of W. Xia, J. Zhang, and H. Zhu was supported in part by the National Natural Science Foundation of China (NSFC) under Grant 61427801, Grant 61671251, and Grant 61771252, in part by the Open Research Fund of the National Mobile Communications Research Laboratory, Southeast University, under Grant 2017D05, and in part by the Nanjing University of Posts and Telecommunications Start-Up Foundation under Grant NY215004. The work of T. Q. S. Quek was supported in part by the MOE ARF Tier 2 under Grant MOE2015-T2-2-104 and in part by the SUTD-ZJU Research Collaboration under Grant SUTD-ZJU/RES/01/2016. The work of S. Jin was supported by NSFC under Grant 61625106 and Grant 61531011. This paper was presented in part at the IEEE Wireless Communications and Networking Conference (WCNC), Barcelona, Spain, April 2018 [1]. The associate editor coordinating the review of this paper and approving it for publication was A. Abrardo. (Corresponding authors: Hongbo Zhu; Jun Zhang.) W. Xia and J. Zhang are with the Jiangsu Key Laboratory of Wireless Communications, Nanjing University of Posts and Telecommunications, Nanjing 210003, China, and also with the National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China (e-mail: [email protected]; [email protected]).
Publisher Copyright:
© 2002-2012 IEEE.
PY - 2018/11
Y1 - 2018/11
N2 - In this paper, we consider the network power minimization problem in a downlink cloud radio access network (C-RAN), taking into account the power consumed at the baseband unit (BBU) for computation and the power consumed at the remote radio heads and fronthaul links for transmission. The power minimization problem for transmission is a fast time-scale issue, whereas the power minimization problem for computation is a slow time-scale issue. Therefore, the joint network power minimization problem is a mixed time-scale problem. To tackle the time-scale challenge, we introduce large system analysis to turn the original fast time-scale problem into a slow time-scale one that only depends on the statistical channel information. In addition, we propose a bound improving branch-and-bound algorithm and a combinational algorithm to find the optimal and suboptimal solutions to the power minimization problem for computation, respectively, and propose an iterative coordinate descent algorithm to find the solutions to the power minimization problem for transmission. Finally, a distributed algorithm based on hierarchical decomposition is proposed to solve the joint network power minimization problem. In summary, this paper provides a framework to investigate how execution efficiency and computing capability at BBU as well as delay constraint of tasks can affect the network power minimization problem in C-RANs.
AB - In this paper, we consider the network power minimization problem in a downlink cloud radio access network (C-RAN), taking into account the power consumed at the baseband unit (BBU) for computation and the power consumed at the remote radio heads and fronthaul links for transmission. The power minimization problem for transmission is a fast time-scale issue, whereas the power minimization problem for computation is a slow time-scale issue. Therefore, the joint network power minimization problem is a mixed time-scale problem. To tackle the time-scale challenge, we introduce large system analysis to turn the original fast time-scale problem into a slow time-scale one that only depends on the statistical channel information. In addition, we propose a bound improving branch-and-bound algorithm and a combinational algorithm to find the optimal and suboptimal solutions to the power minimization problem for computation, respectively, and propose an iterative coordinate descent algorithm to find the solutions to the power minimization problem for transmission. Finally, a distributed algorithm based on hierarchical decomposition is proposed to solve the joint network power minimization problem. In summary, this paper provides a framework to investigate how execution efficiency and computing capability at BBU as well as delay constraint of tasks can affect the network power minimization problem in C-RANs.
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U2 - 10.1109/TWC.2018.2865955
DO - 10.1109/TWC.2018.2865955
M3 - Article
AN - SCOPUS:85052690347
SN - 1536-1276
VL - 17
SP - 7268
EP - 7280
JO - IEEE Transactions on Wireless Communications
JF - IEEE Transactions on Wireless Communications
IS - 11
M1 - 8445710
ER -