To reduce the interference among small cells of Ultra-Dense Networks(UDN),an improved Clustering-Assisted Resource Allocation(CARA)scheme is proposed in this paper.The proposed scheme is divided into three steps.First...To reduce the interference among small cells of Ultra-Dense Networks(UDN),an improved Clustering-Assisted Resource Allocation(CARA)scheme is proposed in this paper.The proposed scheme is divided into three steps.First,an Interference-Limited Clustering Algorithm(ILCA)based on interference graph corresponding to the interference relationship between Femtocell Base Stations(FBSs),is proposed to group FBSs into disjoint clusters,in which a pre-threshold is set to constrain the sum of interference in each cluster,and a Cluster Head(CH)is selected for each cluster.Then,CH performs a twostage sub-channel allocation within its associated cluster,where the first stage assigns one sub-channel to each user of the cluster and the second stage assigns a second sub-channel to some users.Finally,a power allocation method is designed to maximize throughput for a given clustering and sub-channel configuration.Simulation results indicate that the proposed scheme distributes FBSs into each cluster more evenly,and significantly improves the system throughput compared with the existing schemes in the same scenario.展开更多
The research of complex networks facilitates the progress of various disciplines,including biology,chemistry,social science,computer,and communication engineering.Recently,it is popular to utilize complex networks to ...The research of complex networks facilitates the progress of various disciplines,including biology,chemistry,social science,computer,and communication engineering.Recently,it is popular to utilize complex networks to study the communication networks,such as designing efficient routing strategies and robust communication networks.However,exploiting the advantages of communication networks to investigate networks in various disciplines beyond telecommunications is still in infancy.Because of this situation,this paper proposes an information-defined network(IDN)framework by which a complex network can be abstracted as a communication network associated with multiple intelligent agents.Specifically,each component and dynamic process in this framework can be defined by information.We show that the IDN framework promotes the research of unsolved problems in the current complex network field,especially for detecting new interaction types in realworld networks.展开更多
基金performed in the Project “Research on the Hierarchical Interference Elimination Technology for UDN Based on MIMO” supported by the Henan Scientific and Technological Research Project (172102210023)“Research on clustering and frequency band allocation in JT-Co MP supported by Department of Education of Henan Province (19A510013)”
文摘To reduce the interference among small cells of Ultra-Dense Networks(UDN),an improved Clustering-Assisted Resource Allocation(CARA)scheme is proposed in this paper.The proposed scheme is divided into three steps.First,an Interference-Limited Clustering Algorithm(ILCA)based on interference graph corresponding to the interference relationship between Femtocell Base Stations(FBSs),is proposed to group FBSs into disjoint clusters,in which a pre-threshold is set to constrain the sum of interference in each cluster,and a Cluster Head(CH)is selected for each cluster.Then,CH performs a twostage sub-channel allocation within its associated cluster,where the first stage assigns one sub-channel to each user of the cluster and the second stage assigns a second sub-channel to some users.Finally,a power allocation method is designed to maximize throughput for a given clustering and sub-channel configuration.Simulation results indicate that the proposed scheme distributes FBSs into each cluster more evenly,and significantly improves the system throughput compared with the existing schemes in the same scenario.
基金supported in part by Young Elite Scientists Sponsorship Program by CAST under Grant number 2018QNRC001National Science Foundation of China with Grant number 91738202, 62071194
文摘The research of complex networks facilitates the progress of various disciplines,including biology,chemistry,social science,computer,and communication engineering.Recently,it is popular to utilize complex networks to study the communication networks,such as designing efficient routing strategies and robust communication networks.However,exploiting the advantages of communication networks to investigate networks in various disciplines beyond telecommunications is still in infancy.Because of this situation,this paper proposes an information-defined network(IDN)framework by which a complex network can be abstracted as a communication network associated with multiple intelligent agents.Specifically,each component and dynamic process in this framework can be defined by information.We show that the IDN framework promotes the research of unsolved problems in the current complex network field,especially for detecting new interaction types in realworld networks.
