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

Tuyen X. Tran, D. Pompili
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引用次数: 18

Abstract

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 beam forming 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 beam forming 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 beam forming schemes. Additionally, the results also demonstrate the significant improvement in computing-resource utilization of C-RANs over traditional RANs with distributed computing resources.
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基于计算资源共享的下行云局域网动态无线电协作
针对由多个远程无线电头(RRHs)组成的云无线接入网(c - ran),提出了一种新的动态无线电合作策略,该网络连接到一个中央虚拟基站(VBS)池。特别地,利用c - ran在计算资源共享和vbs之间实时通信方面的关键能力,设计了一种联合动态无线电聚类和协同波束形成方案,使下行加权和速率系统效用(WSRSU)最大化。由于无线电聚类过程的组合性和协同波束形成设计的非凸性,其潜在的优化问题是np困难的,对于大型网络来说是极难解决的。我们的方法旨在通过将原始问题转化为混合整数二阶锥规划(MI-SOCP)来获得次优解,并可以使用所提出的迭代算法有效地求解。数值模拟结果表明,该算法在WSRSU方面提供了接近最优的性能,同时显著优于传统的无线电聚类和波束形成方案。此外,结果还表明,与具有分布式计算资源的传统ran相比,c - ran的计算资源利用率有显著提高。
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