针对云无线网络(Cloud Radio Access Network,C-RAN)中传统静态资源分配效率低下以及动态无线资源分配中资源种类单一的问题,提出了一种基于用户服务质量(Qulity of Service,QoS)约束的动态无线资源分配方案,对无线资源从无线射频单元(R...针对云无线网络(Cloud Radio Access Network,C-RAN)中传统静态资源分配效率低下以及动态无线资源分配中资源种类单一的问题,提出了一种基于用户服务质量(Qulity of Service,QoS)约束的动态无线资源分配方案,对无线资源从无线射频单元(Remote Radio Head,RRH)选择、子载波分配和RRH功率分配三个维度进行研究。首先,根据传统的C-RAN系统传输模型和QoS约束在时变业务环境下建立了以发射功率为变量,以吞吐量最大为优化目标的优化问题;然后,基于改进的遗传算法,将原优化方案转变为通过优化RRH选择、子载波分配和RRH功率分配来达到提高系统吞吐量的目的;最后,将改进的遗传算法与其他智能算法在种群规模变化下进行了时间复杂度对比。实验结果表明,所提算法具有较低时间复杂度,所提资源分配方案下的平均吞吐量增益为17%。展开更多
The key technologies involved in the evolution of the Cloud-based Radio Access Network(C-RAN) are discussed in this paper. Taking the Frameless Network Architecture(FNA) as a starting point, a cell-lessbased network t...The key technologies involved in the evolution of the Cloud-based Radio Access Network(C-RAN) are discussed in this paper. Taking the Frameless Network Architecture(FNA) as a starting point, a cell-lessbased network topology for a multi-tier Heterogeneous Network(Het Net) and ultra-dense network is proposed. The FNA network topology modeling is researched with centralized processing and distributed antenna deployments. The Antenna Element(AE) is released as a new dimensional radio resource that is included in the centralized Radio Resource Management(RRM) processes. This contributes to the on-demand user-centric serving-set associations with cell-edge effect elimination. The Control Plane(CP) and User Plane(UP) separation and adaptation are introduced for energy efficiency improvements. The centralized RRM and different optimization goals are discussed for fully exploring the merits from the centralized computing of C-RAN. Considering the complexity, near-optimal approaches for specific users' Quality-of-Service(Qo S) requirements are addressed. Finally, based on the research highlighted above, the way forward of C-RAN evolution is discussed.展开更多
提出了一种云无线接入网络(C-RAN, cloud radio access network)安全通信系统下行资源分配算法,该算法在满足物联网信息终端的信干噪比、物联网窃听终端信干噪比和前向链路容量等约束条件下,通过联合优化基站模式、量化噪声和波束成形...提出了一种云无线接入网络(C-RAN, cloud radio access network)安全通信系统下行资源分配算法,该算法在满足物联网信息终端的信干噪比、物联网窃听终端信干噪比和前向链路容量等约束条件下,通过联合优化基站模式、量化噪声和波束成形等参数实现系统功率最小化。此设计是一个非凸优化问题,为了有效求解该问题,采用分步优化方法将原问题进行分解。提出利用半定松弛技术和函数平滑方法,并通过迭代差分凸函数法求得原问题的次优解。通过二分法确定基站模式,再优化基站发射功率。仿真结果表明,所提联合优化算法相比组稀疏优化算法和基准算法具有更好的性能,且其性能接近穷举法。展开更多
摘要针对云无线网络(Cloud Radio Access Network,C-RAN)中传统静态资源分配效率低下以及动态无线资源分配中资源种类单一的问题,提出了一种基于用户服务质量(Qulity of Service,QoS)约束的动态无线资源分配方案,对无线资源从无线射频单元(Remote Radio Head,RRH)选择、子载波分配和RRH功率分配三个维度进行研究。首先,根据传统的C-RAN系统传输模型和QoS约束在时变业务环境下建立了以发射功率为变量,以吞吐量最大为优化目标的优化问题;然后,基于改进的遗传算法,将原优化方案转变为通过优化RRH选择、子载波分配和RRH功率分配来达到提高系统吞吐量的目的;最后,将改进的遗传算法与其他智能算法在种群规模变化下进行了时间复杂度对比。实验结果表明,所提算法具有较低时间复杂度,所提资源分配方案下的平均吞吐量增益为17%。
基金supported by the National High Technology Research and Development Program of China No.2014AA01A701Nature and Science Foundation of China under Grants No.61471068,61421061+2 种基金Beijing Nova Programme No.Z131101000413030International Collaboration Project No.2015DFT10160National Major Project No.2016ZX03001009-003
摘要The key technologies involved in the evolution of the Cloud-based Radio Access Network(C-RAN) are discussed in this paper. Taking the Frameless Network Architecture(FNA) as a starting point, a cell-lessbased network topology for a multi-tier Heterogeneous Network(Het Net) and ultra-dense network is proposed. The FNA network topology modeling is researched with centralized processing and distributed antenna deployments. The Antenna Element(AE) is released as a new dimensional radio resource that is included in the centralized Radio Resource Management(RRM) processes. This contributes to the on-demand user-centric serving-set associations with cell-edge effect elimination. The Control Plane(CP) and User Plane(UP) separation and adaptation are introduced for energy efficiency improvements. The centralized RRM and different optimization goals are discussed for fully exploring the merits from the centralized computing of C-RAN. Considering the complexity, near-optimal approaches for specific users' Quality-of-Service(Qo S) requirements are addressed. Finally, based on the research highlighted above, the way forward of C-RAN evolution is discussed.
摘要提出了一种云无线接入网络(C-RAN, cloud radio access network)安全通信系统下行资源分配算法,该算法在满足物联网信息终端的信干噪比、物联网窃听终端信干噪比和前向链路容量等约束条件下,通过联合优化基站模式、量化噪声和波束成形等参数实现系统功率最小化。此设计是一个非凸优化问题,为了有效求解该问题,采用分步优化方法将原问题进行分解。提出利用半定松弛技术和函数平滑方法,并通过迭代差分凸函数法求得原问题的次优解。通过二分法确定基站模式,再优化基站发射功率。仿真结果表明,所提联合优化算法相比组稀疏优化算法和基准算法具有更好的性能,且其性能接近穷举法。