支持D2D的下行雾无线接入网联合模式选择和资源分配

Hongyu Xiang, M. Peng, Yuanyuan Cheng, Hsiao-Hwa Chen
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引用次数: 29

摘要

云无线接入网(c - ran)作为一种将云计算纳入无线接入网的创新范例,在减少资本和运营支出以及为客户提供更好的服务方面具有优势。然而,非理想前传的沉重负担限制了c - ran的性能。在这里,我们着重于通过边缘设备的缓存来减轻前传的负担,并提出了一种基于雾计算的RAN (F-RAN)架构,该架构具有三种候选传输模式:设备到设备、本地分布式协调和全局C-RAN。在此基础上,给出了考虑拥塞控制的系统优化问题的平均能源效率(EE)。在Lyapunov框架下,将该问题重新表述为一个联合模式选择和资源分配问题,并采用块坐标下降法求解。数学分析和仿真结果验证了F-RAN的优点,该算法可以实现EE-delay的折衷。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Joint mode selection and resource allocation for downlink fog radio access networks supported D2D
Presented as an innovative paradigm incorporating the cloud computing into radio access network, cloud radio access networks (C-RANs) have been shown advantageous in curtailing the capital and operating expenditures as well as providing better services to the customers. However, heavy burden on the non-ideal fronthaul limits performances of C-RANs. Here we focus on the alleviation of burden on the fronthaul via the edge devices' caches and propose a fog computing based RAN (F-RAN) architecture with three candidate transmission modes: device to device, local distributed coordination, and global C-RAN. Followed by the proposed simple mode selection scheme, the average energy efficiency (EE) of systems optimization problem considering congestion control is presented. Under the Lyapunov framework, the problem is reformulated as a joint mode selection and resource allocation problem, which can be solved by block coordinate descent method. The mathematical analysis and simulation results validate the benefits of F-RAN and an EE-delay tradeoff can be achieved by the proposed algorithm.
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