Joint Scheduling and Beamforming Coordination in Cloud Radio Access Networks With QoS Guarantees

• Published in: IEEE transactions on vehicular technology Vol. 65; no. 7; pp. 5449 - 5460
• Main Authors: Huang, Xiaoyan, Xue, Guoliang, Yu, Ruozhou, Leng, Supeng
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Array signal processing; Beamforming; Cloud computing; cloud radio access network (C-RAN); Efficiency; Heuristic algorithms; Interference; Joints; MIMO; multiuser multiple-input multiple-output (MIMO); Networks; Optimization; Quality of service; Quality of service architectures; Radio; scheduling; Utilities; wireless networks
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2015.2464278

The cloud radio access network (C-RAN) is a promising architecture for future radio access networks (RANs) due to its advantages in cost efficiency, flexibility, and utilization efficiency. To fully reap these benefits, this paper focuses on joint optimization of user grouping, virtual base station (VBS) clustering, and transmit beamforming in C-RAN downlink networks for maximizing the system utility, subject to the diverse quality-of-service (QoS) requirements of users and the power constraints of distributed remote radio heads (RRHs). To tackle the high computational complexity in solving the nonconvex combinatorial optimization problem, a two-stage solution is proposed. Specifically, a dynamic user-centric scheduling algorithm is developed to form user groups and cluster RRHs into VBSs by exploiting the nonuniform distribution of users. Then, an iterative transmit beamformer optimization algorithm is devised to coordinate the transmit beamforming among the VBSs to mitigate the intracell and intercell interference, hence further enhancing the overall system utility. Evaluation results demonstrate that the proposed algorithm achieves significant performance gain over various reference algorithms in terms of system utility, system throughput, and energy efficiency.