软件定义超蜂窝网络中的通信与计算协同优化
发布时间：2019-06-12 08:07
【摘要】：近年提出的云无线接入网,通过集中化改善了小区为中心无线接入网在成本和灵活性方面的瓶颈.但是,云无线接入网需要通过前传网大范围汇聚带宽极高的前传采样,造成了过高的建设与运营成本.本文针对云无线接入网过度依赖前传通信资源的问题,依据控制与数据分离的思想设计了一种软件定义超蜂窝网络新型架构,并提出了在该架构下通过通信与计算协同的资源部署大幅降低前传汇聚带宽的具体方案.首先基于排队论给出了虚拟基站池中计算资源统计复用增益与池规模的定量关系,并依据统计复用增益边际效应迅速递减的性质得到了部署中等规模基站池更经济的指导方针.然后基于图聚类框架针对基带处理功能分割部署问题给出了一种遗传算法,该算法给出的分割方案可以根据设计偏好在前传带宽成本与计算代价间进行灵活折衷.
[Abstract]:The cloud wireless access network proposed in recent years improves the bottleneck of cost and flexibility of cell-centered wireless access network through centralization. However, the cloud wireless access network needs to collect the pretransmission sampling with very high bandwidth through the pre-transmission network, which results in too high construction and operation costs. In order to solve the problem that cloud wireless access network relies too much on pre-transmission communication resources, a new software-defined super-cellular network architecture is designed according to the idea of separation of control and data, and a concrete scheme to greatly reduce the pretransmission convergence bandwidth through the collaborative resource deployment of communication and computing under this architecture is proposed. Firstly, based on the queuing theory, the quantitative relationship between the statistical reuse gain of computing resources and the pool size in the virtual base station pool is given, and the more economical guidelines for deploying the medium scale base station pool are obtained according to the property of the rapidly decreasing marginal effect of the statistical reuse gain. Then, based on the graph clustering framework, a genetic algorithm is proposed to solve the problem of baseband processing functional segmentation deployment. The proposed segmentation scheme can make a flexible compromise between the pretransmission bandwidth cost and the computational cost according to the design preference.
【作者单位】： 清华大学电子工程系;清华大学信息科学与技术国家实验室(筹);
【基金】：国家重点基础研究发展计划(973)(批准号:2012CB316000) 国家自然科学基金(批准号:61461136004,61571265,91638204)资助项目
【分类号】：TN929.5
[Abstract]:The cloud wireless access network proposed in recent years improves the bottleneck of cost and flexibility of cell-centered wireless access network through centralization. However, the cloud wireless access network needs to collect the pretransmission sampling with very high bandwidth through the pre-transmission network, which results in too high construction and operation costs. In order to solve the problem that cloud wireless access network relies too much on pre-transmission communication resources, a new software-defined super-cellular network architecture is designed according to the idea of separation of control and data, and a concrete scheme to greatly reduce the pretransmission convergence bandwidth through the collaborative resource deployment of communication and computing under this architecture is proposed. Firstly, based on the queuing theory, the quantitative relationship between the statistical reuse gain of computing resources and the pool size in the virtual base station pool is given, and the more economical guidelines for deploying the medium scale base station pool are obtained according to the property of the rapidly decreasing marginal effect of the statistical reuse gain. Then, based on the graph clustering framework, a genetic algorithm is proposed to solve the problem of baseband processing functional segmentation deployment. The proposed segmentation scheme can make a flexible compromise between the pretransmission bandwidth cost and the computational cost according to the design preference.
【作者单位】： 清华大学电子工程系;清华大学信息科学与技术国家实验室(筹);
【基金】：国家重点基础研究发展计划(973)(批准号:2012CB316000) 国家自然科学基金(批准号:61461136004,61571265,91638204)资助项目
【分类号】：TN929.5
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