TY - JOUR
T1 - A distributed approach to improving spectral efficiency in uplink device-to-device-enabled cloud radio access networks
AU - Sun, Yaohua
AU - Peng, Mugen
AU - Poor, H. Vincent
N1 - Funding Information:
Manuscript received September 15, 2017; revised February 3, 2018 and June 8, 2018; accepted June 30, 2018. Date of publication July 12, 2018; date of current version December 14, 2018. This work was supported in part by the Chinese State Major Science and Technology Special Project under Grant 2016ZX03001020-006 and 2017ZX03001025-006, in part by the Chinese National Program for Special Support of Eminent Professionals, and in part by the U.S. National Science Foundation under Grants CNS-1702808 and ECCS-1647198. This paper was presented in part at the 2016 IEEE Global Communications Conference. The associate editor coordinating the review of this paper and approving it for publication was J. Choi. (Corresponding author: Mugen Peng.) Y. Sun and M. Peng are with the Key Laboratory of Universal Wireless Communications (Ministry of Education), Beijing University of Posts and Telecommunications, Beijing 100876, China (e-mail: sunyaohua@ bupt.edu.cn; pmg@bupt.edu.cn).
Publisher Copyright:
© 1972-2012 IEEE.
PY - 2018/12
Y1 - 2018/12
N2 - Device-to-device (D2D)-enabled cloud radio access networks (C-RANs) are potential solutions for further improving spectral efficiency (SE) and decreasing latency by allowing direct communication between two users. However, due to the need to acquire global channel state information (CSI) and to execute centralized algorithms, heavy burdens are placed on the fronthaul and the baseband unit (BBU) pool. To alleviate these burdens, a distributed approach to mode selection and resource allocation for potential D2D pairs under pre-determined resource allocation of C-RAN users is proposed, in which pairs of users are endowed with decision-making capabilities. The proposed procedure is divided into three stages: Communication mode and subchannel selection, utility value determination, and reinforcement-learning-based strategy update. The core idea is that the D2D pairs self-optimize the mode selection and resource allocation without global CSI under several practical constraints. Simulation results show that enabling D2D can significantly improve SE for C-RANs. Furthermore, the impacts of the fronthaul capacity, the centralized signal processing capability of the BBU pool, and the distance between the D2D transmitter and the remote radio head are demonstrated and analyzed.
AB - Device-to-device (D2D)-enabled cloud radio access networks (C-RANs) are potential solutions for further improving spectral efficiency (SE) and decreasing latency by allowing direct communication between two users. However, due to the need to acquire global channel state information (CSI) and to execute centralized algorithms, heavy burdens are placed on the fronthaul and the baseband unit (BBU) pool. To alleviate these burdens, a distributed approach to mode selection and resource allocation for potential D2D pairs under pre-determined resource allocation of C-RAN users is proposed, in which pairs of users are endowed with decision-making capabilities. The proposed procedure is divided into three stages: Communication mode and subchannel selection, utility value determination, and reinforcement-learning-based strategy update. The core idea is that the D2D pairs self-optimize the mode selection and resource allocation without global CSI under several practical constraints. Simulation results show that enabling D2D can significantly improve SE for C-RANs. Furthermore, the impacts of the fronthaul capacity, the centralized signal processing capability of the BBU pool, and the distance between the D2D transmitter and the remote radio head are demonstrated and analyzed.
KW - Cloud radio access networks (C-RANs)
KW - device-to-device (D2D)
KW - game theory
KW - mode selection
KW - resource allocation
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U2 - 10.1109/TCOMM.2018.2855212
DO - 10.1109/TCOMM.2018.2855212
M3 - Article
AN - SCOPUS:85049972823
SN - 1558-0857
VL - 66
SP - 6511
EP - 6526
JO - IEEE Transactions on Communications
JF - IEEE Transactions on Communications
IS - 12
M1 - 8410619
ER -