Dynamic Radio Cooperation for User User-Centric Cloud-RAN RAN With Computing Resource Sharing
Abstract: A novel dynamic radio-cooperation cooperation strategy is proposed for a Cloud Radio Access Network (Cloud-RAN) RAN) consisting of multiple Remote Radio Heads connected to a central Virtual Base Station (VBS) pool. In particular, the key capabilities of CloudCloud RAN in computing-resource resource sharing and real real-time 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 Sum System Utility (WSRSU). Due to the combinatorial natur nature e of the radio clustering process and to the non-convexity convexity of the cooperative beamforming design, the underlying optimization problem is NP NP-hard, hard, and is extremely difficult to solve for a large network. The proposed approach aims for a suboptimal solution by transforming the original problem into a Mixed Mixed-Integer Second-Order Order Cone Program (MI-SOCP) (MI and applying Sequential Convex Approximation (SCA) to derive a novel iterative algorithm. Numerical simulation results show that our low low-complexity complexity algorithm provides near-optimal 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 resource utilization of Cloud Cloud-RAN over ver a traditional RAN with distributed computing resources.