Dynamic Radio Cooperation for Downlink Cloud-RANs with Computing Resource Sharing

A novel dynamic radio-cooperation strategy is proposed for Cloud Radio Access Networks (C-RANs) consisting of multiple Remote Radio Heads (RRHs) connected to a central Virtual Base Station (VBS) pool. In particular, the key capabilities of C-RANs in computing-resource sharing and real-time communication among the VBSs are leveraged to design a joint dynamic radio clustering and cooperative beamforming scheme that maximizes the downlink weighted sum-rate system utility (WSRSU). Due to the combinatorial nature of the radio clustering process and the non-convexity of the cooperative beamforming design, the underlying optimization problem is NP-hard, and is extremely difficult to solve for a large network. Our approach aims for a suboptimal solution by transforming the original problem into a Mixed-Integer Second-Order Cone Program (MI-SOCP), which can be solved efficiently using a proposed iterative algorithm. Numerical simulation results show that our low-complexity algorithm provides close-to-optimal performance in terms of WSRSU while significantly outperforming conventional radio clustering and beamforming schemes. Additionally, the results also demonstrate the significant improvement in computing-resource utilization of C-RANs over traditional RANs with distributed computing resources.Comment: 9 pages, 6 figures, accepted to IEEE MASS 201

Understanding the Computational Requirements of Virtualized Baseband Units using a Programmable Cloud Radio Access Network Testbed

Cloud Radio Access Network (C-RAN) is emerging as a transformative architecture for the next generation of mobile cellular networks. In C-RAN, the Baseband Unit (BBU) is decoupled from the Base Station (BS) and consolidated in a centralized processing center. While the potential benefits of C-RAN have been studied extensively from the theoretical perspective, there are only a few works that address the system implementation issues and characterize the computational requirements of the virtualized BBU. In this paper, a programmable C-RAN testbed is presented where the BBU is virtualized using the OpenAirInterface (OAI) software platform, and the eNodeB and User Equipment (UEs) are implemented using USRP boards. Extensive experiments have been performed in a FDD downlink LTE emulation system to characterize the performance and computing resource consumption of the BBU under various conditions. It is shown that the processing time and CPU utilization of the BBU increase with the channel resources and with the Modulation and Coding Scheme (MCS) index, and that the CPU utilization percentage can be well approximated as a linear increasing function of the maximum downlink data rate. These results provide real-world insights into the characteristics of the BBU in terms of computing resource and power consumption, which may serve as inputs for the design of efficient resource-provisioning and allocation strategies in C-RAN systems.Comment: In Proceedings of the IEEE International Conference on Autonomic Computing (ICAC), July 201