To fulfill the explosive growth of network capacity, fifth generation(5G) standard has captured the attention and imagination of researchers and engineers around the world. In particular, heterogeneous cloud radio acc...To fulfill the explosive growth of network capacity, fifth generation(5G) standard has captured the attention and imagination of researchers and engineers around the world. In particular, heterogeneous cloud radio access network(H-CRAN), as a promising network paradigm in 5G system, is a hot research topic in recent years. However, the densely deployment of RRHs in H-CRAN leads to downlink/uplink traffic asymmetry and severe inter-cell interference which could seriously impair the network throughput and resource utilization. To simultaneously solve these two problems, we proposed a dynamic resource allocation(DRA) scheme for H-CRAN in TDD mode. Firstly, we design a clustering algorithm to group the RRHs into different sets. Secondly, we adopt coordinated multipoint technology to eliminate the interference in each set. Finally, we formulate the joint frame structure, power and subcarrier selection problem as a mixed strategy noncooperative game. The simulation results are presented to validate the effectiveness of our proposed algorithm by compared with the existing work.展开更多
In order to enhance the efficiency of spectrum utilization and reduce communication overhead in spectrum sharing process, we propose a two-stage dynamic spectrum sharing scheme in which cooperative and noncooperative ...In order to enhance the efficiency of spectrum utilization and reduce communication overhead in spectrum sharing process, we propose a two-stage dynamic spectrum sharing scheme in which cooperative and noncooperative modes are analyzed in both stages. In particular, the existence and the uniqueness of Nash Equilibrium(NE) strategies for noncooperative mode are proved. In addition, a distributed iterative algorithm is proposed to obtain the optimal solutions of the scheme. Simulation studies are carried out to show the performance comparison between two modes as well as the system revenue improvement of the proposed scheme compared with a conventional scheme without a virtual price control factor.展开更多
The rapid development of network technology and its evolution toward heterogeneous networks has increased the demand to support automatic monitoring and the management of heterogeneous wireless communication networks....The rapid development of network technology and its evolution toward heterogeneous networks has increased the demand to support automatic monitoring and the management of heterogeneous wireless communication networks.This paper presents a multilevel pattern mining architecture to support automatic network management by discovering interesting patterns from telecom network monitoring data.This architecture leverages and combines existing frequent itemset discovery over data streams,association rule deduction,frequent sequential pattern mining,and frequent temporal pattern mining techniques while also making use of distributed processing platforms to achieve high-volume throughput.展开更多
基金jointly supported by Project 61501052 and 61302080 of the National Natural Science Foundation of China
文摘To fulfill the explosive growth of network capacity, fifth generation(5G) standard has captured the attention and imagination of researchers and engineers around the world. In particular, heterogeneous cloud radio access network(H-CRAN), as a promising network paradigm in 5G system, is a hot research topic in recent years. However, the densely deployment of RRHs in H-CRAN leads to downlink/uplink traffic asymmetry and severe inter-cell interference which could seriously impair the network throughput and resource utilization. To simultaneously solve these two problems, we proposed a dynamic resource allocation(DRA) scheme for H-CRAN in TDD mode. Firstly, we design a clustering algorithm to group the RRHs into different sets. Secondly, we adopt coordinated multipoint technology to eliminate the interference in each set. Finally, we formulate the joint frame structure, power and subcarrier selection problem as a mixed strategy noncooperative game. The simulation results are presented to validate the effectiveness of our proposed algorithm by compared with the existing work.
基金supported in part by the National Natural Science Foundation of China(61471115)the National Science and Technology Major Project of the Ministry of Science and Technology of China(2014ZX03003010-002)+1 种基金the General Program of Natural Science Foundation of Jiangsu Province(BK20131299)the 2016 Science and Technology joint research and innovation foundation of Jiangsu province(SBY2016020323)
文摘In order to enhance the efficiency of spectrum utilization and reduce communication overhead in spectrum sharing process, we propose a two-stage dynamic spectrum sharing scheme in which cooperative and noncooperative modes are analyzed in both stages. In particular, the existence and the uniqueness of Nash Equilibrium(NE) strategies for noncooperative mode are proved. In addition, a distributed iterative algorithm is proposed to obtain the optimal solutions of the scheme. Simulation studies are carried out to show the performance comparison between two modes as well as the system revenue improvement of the proposed scheme compared with a conventional scheme without a virtual price control factor.
基金funded by the Enterprise Ireland Innovation Partnership Programme with Ericsson under grant agreement IP/2011/0135[6]supported by the National Natural Science Foundation of China(No.61373131,61303039,61232016,61501247)+1 种基金the PAPDCICAEET funds
文摘The rapid development of network technology and its evolution toward heterogeneous networks has increased the demand to support automatic monitoring and the management of heterogeneous wireless communication networks.This paper presents a multilevel pattern mining architecture to support automatic network management by discovering interesting patterns from telecom network monitoring data.This architecture leverages and combines existing frequent itemset discovery over data streams,association rule deduction,frequent sequential pattern mining,and frequent temporal pattern mining techniques while also making use of distributed processing platforms to achieve high-volume throughput.
