Recently,the Fog-Radio Access Network(F-RAN)has gained considerable attention,because of its flexible architecture that allows rapid response to user requirements.In this paper,computational offloading in F-RAN is con...Recently,the Fog-Radio Access Network(F-RAN)has gained considerable attention,because of its flexible architecture that allows rapid response to user requirements.In this paper,computational offloading in F-RAN is considered,where multiple User Equipments(UEs)offload their computational tasks to the F-RAN through fog nodes.Each UE can select one of the fog nodes to offload its task,and each fog node may serve multiple UEs.The tasks are computed by the fog nodes or further offloaded to the cloud via a capacity-limited fronhaul link.In order to compute all UEs'tasks quickly,joint optimization of UE-Fog association,radio and computation resources of F-RAN is proposed to minimize the maximum latency of all UEs.This min-max problem is formulated as a Mixed Integer Nonlinear Program(MINP).To tackle it,first,MINP is reformulated as a continuous optimization problem,and then the Majorization Minimization(MM)method is used to find a solution.The MM approach that we develop is unconventional in that each MM subproblem is solved inexactly with the same provable convergence guarantee as the exact MM,thereby reducing the complexity of MM iteration.In addition,a cooperative offloading model is considered,where the fog nodes compress-and-forward their received signals to the cloud.Under this model,a similar min-max latency optimization problem is formulated and tackled by the inexact MM.Simulation results show that the proposed algorithms outperform some offloading strategies,and that the cooperative offloading can exploit transmission diversity better than noncooperative offloading to achieve better latency performance.展开更多
针对现有通过设计一体化波束的安全传输方法,难以应对信息传输过程中的信息泄露、非法窃听和恶意攻击等安全性问题,充分利用人工噪声自由度,提出了一种基于人工噪声的通信感知一体化(Integrated Sensing and Communication,ISAC)安全传...针对现有通过设计一体化波束的安全传输方法,难以应对信息传输过程中的信息泄露、非法窃听和恶意攻击等安全性问题,充分利用人工噪声自由度,提出了一种基于人工噪声的通信感知一体化(Integrated Sensing and Communication,ISAC)安全传输方法。该方法的设计目标是在目标感知信噪比和一体化基站发射功率满足系统设计的需求下,通过设计一体化基站的预编码矩阵和人工噪声矢量来最大化信息传输的保密率。上述优化问题受复杂的香农保密率目标函数的限制,获取该非凸优化问题的解非常困难,提出一种基于加权均方最小误差(Weighted Minimum Mean Square Error,WMMSE)的半定规划(Semi-Definite Programming,SDP)迭代算法。该算法利用WMMSE与信道容量之间的关系,对复杂的保密率进行等价转化,采用基于SDP的交替迭代算法来获取一体化基站预编码矩阵和人工噪声矢量。实验结果表明,相比于没有添加人工噪声的传统方法,基于人工噪声的ISAC安全传输方法能够有效地提高信息传输的保密率。所提方法为ISAC系统信息传输的安全性研究提供了理论和实践参考。展开更多
云无线接入网络(cloud radio access network,C-RAN)是一种能够集中处理信号的网络架构。C-RAN能够通过算法动态选择无线电单元(remote radio head,RRH)来调整用户通信速率。而通信速率作为用户服务质量(quality of service,QoS)的关键...云无线接入网络(cloud radio access network,C-RAN)是一种能够集中处理信号的网络架构。C-RAN能够通过算法动态选择无线电单元(remote radio head,RRH)来调整用户通信速率。而通信速率作为用户服务质量(quality of service,QoS)的关键部分,当参与服务的RRH越多时,用户的通信速率更大且体验更好,但同时所带来的能源损耗越大,因此本文研究通信速率和功率消耗二者之间的权衡关系。提出一种优化算法,将权衡问题建模成一个单目标优化模型,通过权衡系数来协调速率和RRH激活个数之间的矛盾。为了解决l0-范数的非凸问题,本文使用重复加权l1-范数去近似l0-范数,同时使用加权最小均方误差(weighted minimum mean square error,WMMSE)的方法将通信速率从非凸问题转换成一个凸问题,最后使用改进的次梯度法对预编码矩阵进行更新。仿真结果证明该算法减少了时间复杂度,同时达到了与穷举法相近的性能。展开更多
基金supported in part by the Natural Science Foundation of China (62171110,U19B2028 and U20B2070)。
文摘Recently,the Fog-Radio Access Network(F-RAN)has gained considerable attention,because of its flexible architecture that allows rapid response to user requirements.In this paper,computational offloading in F-RAN is considered,where multiple User Equipments(UEs)offload their computational tasks to the F-RAN through fog nodes.Each UE can select one of the fog nodes to offload its task,and each fog node may serve multiple UEs.The tasks are computed by the fog nodes or further offloaded to the cloud via a capacity-limited fronhaul link.In order to compute all UEs'tasks quickly,joint optimization of UE-Fog association,radio and computation resources of F-RAN is proposed to minimize the maximum latency of all UEs.This min-max problem is formulated as a Mixed Integer Nonlinear Program(MINP).To tackle it,first,MINP is reformulated as a continuous optimization problem,and then the Majorization Minimization(MM)method is used to find a solution.The MM approach that we develop is unconventional in that each MM subproblem is solved inexactly with the same provable convergence guarantee as the exact MM,thereby reducing the complexity of MM iteration.In addition,a cooperative offloading model is considered,where the fog nodes compress-and-forward their received signals to the cloud.Under this model,a similar min-max latency optimization problem is formulated and tackled by the inexact MM.Simulation results show that the proposed algorithms outperform some offloading strategies,and that the cooperative offloading can exploit transmission diversity better than noncooperative offloading to achieve better latency performance.
文摘针对现有通过设计一体化波束的安全传输方法,难以应对信息传输过程中的信息泄露、非法窃听和恶意攻击等安全性问题,充分利用人工噪声自由度,提出了一种基于人工噪声的通信感知一体化(Integrated Sensing and Communication,ISAC)安全传输方法。该方法的设计目标是在目标感知信噪比和一体化基站发射功率满足系统设计的需求下,通过设计一体化基站的预编码矩阵和人工噪声矢量来最大化信息传输的保密率。上述优化问题受复杂的香农保密率目标函数的限制,获取该非凸优化问题的解非常困难,提出一种基于加权均方最小误差(Weighted Minimum Mean Square Error,WMMSE)的半定规划(Semi-Definite Programming,SDP)迭代算法。该算法利用WMMSE与信道容量之间的关系,对复杂的保密率进行等价转化,采用基于SDP的交替迭代算法来获取一体化基站预编码矩阵和人工噪声矢量。实验结果表明,相比于没有添加人工噪声的传统方法,基于人工噪声的ISAC安全传输方法能够有效地提高信息传输的保密率。所提方法为ISAC系统信息传输的安全性研究提供了理论和实践参考。
文摘云无线接入网络(cloud radio access network,C-RAN)是一种能够集中处理信号的网络架构。C-RAN能够通过算法动态选择无线电单元(remote radio head,RRH)来调整用户通信速率。而通信速率作为用户服务质量(quality of service,QoS)的关键部分,当参与服务的RRH越多时,用户的通信速率更大且体验更好,但同时所带来的能源损耗越大,因此本文研究通信速率和功率消耗二者之间的权衡关系。提出一种优化算法,将权衡问题建模成一个单目标优化模型,通过权衡系数来协调速率和RRH激活个数之间的矛盾。为了解决l0-范数的非凸问题,本文使用重复加权l1-范数去近似l0-范数,同时使用加权最小均方误差(weighted minimum mean square error,WMMSE)的方法将通信速率从非凸问题转换成一个凸问题,最后使用改进的次梯度法对预编码矩阵进行更新。仿真结果证明该算法减少了时间复杂度,同时达到了与穷举法相近的性能。
