A cognitive relay network model is proposed, which is defined by a source, a destination, a cognitive relay node and a primary user. The source is assisted by the cognitive relay node which is allowed to coexist with ...A cognitive relay network model is proposed, which is defined by a source, a destination, a cognitive relay node and a primary user. The source is assisted by the cognitive relay node which is allowed to coexist with the primary user by imposing severe constraints on the transmission power so that the quality of service of the primary user is not degraded by the interference caused by the secondary user. The effect of the cognitive relay node on the proposed cognitive relay network model is studied by evaluating the outage probability under interference power constraints for different fading environments. A relay transmission scheme, namely, decode-and-forward is considered. For both the peak and average interference power constraints, the closed-form outage expressions are derived over different channel fading models. Finally, the analytical outage probability expressions are validated through simulations. The results indicate that the proposed model has better outage probability than direct transmission. It is also found that the outage probability decreases with the increase of interference power constraints. Meanwhile, the outage probability under the average interference power constraint is much less than that under the peak interference power constraint when the average interference power constraint is equal to the peak interference power constraint.展开更多
Community detection has attracted a great deal of attention in recent years. A parsimony criterion for detecting this structure means that as minimal as possible number of inserted and deleted edges is needed when we ...Community detection has attracted a great deal of attention in recent years. A parsimony criterion for detecting this structure means that as minimal as possible number of inserted and deleted edges is needed when we make the network considered become a disjoint union of cliques. However, many small groups of nodes are obtained by directly using this criterion to some networks especially for sparse ones. In this paper we propose a weighted parsimony model in which a weight coefficient is introduced to balance the inserted and deleted edges to ensure the obtained subgraphs to be reasonable communities. Some benchmark testing examples are used to validate the effectiveness of the proposed method. It is interesting that the weight here can be determined only by the topological features of the network. Meanwhile we make some comparison of our model with maximizing modularity Q and modularity density D on some of the benchmark networks, although sometimes too many or a little less numbers of communities are obtained with Q or D, a proper number of communities are detected with the weighted model. All the computational results confirm its capability for community detection for the small or middle size networks.展开更多
Generalized Farey tree network （GFTN） and generalized Farey organized pyramid network （CFOPN） model are proposed, and their topological characteristics are studied by both theoretical analysis and numerical simula...Generalized Farey tree network （GFTN） and generalized Farey organized pyramid network （CFOPN） model are proposed, and their topological characteristics are studied by both theoretical analysis and numerical simulations, which are in good accordance with each other. Then weighted GFTN is studied using cumulative distributions of its Farey number value, edge weight, and node strength. These results maybe helpful for future theoretical development of hybrid models.展开更多
基金Supported by National Natural Science Foundation of China (No. 60972039, 60905040 and 60972041 )National High Technology Research and Development Program of China (No. 2009AA01Z241)+3 种基金National Postdoctoral Research Program (No. 20090451239)Important National Science and Technology Specific Projects of China (No. 2009ZX03003-006)Scientific Research Foundation of Nanjing University of Posts and Telecommunications (No. NY210006)Key Teaching Reform Foundation of NUPT (No. JG00210JX01)
文摘A cognitive relay network model is proposed, which is defined by a source, a destination, a cognitive relay node and a primary user. The source is assisted by the cognitive relay node which is allowed to coexist with the primary user by imposing severe constraints on the transmission power so that the quality of service of the primary user is not degraded by the interference caused by the secondary user. The effect of the cognitive relay node on the proposed cognitive relay network model is studied by evaluating the outage probability under interference power constraints for different fading environments. A relay transmission scheme, namely, decode-and-forward is considered. For both the peak and average interference power constraints, the closed-form outage expressions are derived over different channel fading models. Finally, the analytical outage probability expressions are validated through simulations. The results indicate that the proposed model has better outage probability than direct transmission. It is also found that the outage probability decreases with the increase of interference power constraints. Meanwhile, the outage probability under the average interference power constraint is much less than that under the peak interference power constraint when the average interference power constraint is equal to the peak interference power constraint.
基金This research is partially supported by the National Natural Science Foundation of China under Grant No. 60873205, Innovation Project of Chinese Academy of Sciences, kjcsyw-sT.
文摘Community detection has attracted a great deal of attention in recent years. A parsimony criterion for detecting this structure means that as minimal as possible number of inserted and deleted edges is needed when we make the network considered become a disjoint union of cliques. However, many small groups of nodes are obtained by directly using this criterion to some networks especially for sparse ones. In this paper we propose a weighted parsimony model in which a weight coefficient is introduced to balance the inserted and deleted edges to ensure the obtained subgraphs to be reasonable communities. Some benchmark testing examples are used to validate the effectiveness of the proposed method. It is interesting that the weight here can be determined only by the topological features of the network. Meanwhile we make some comparison of our model with maximizing modularity Q and modularity density D on some of the benchmark networks, although sometimes too many or a little less numbers of communities are obtained with Q or D, a proper number of communities are detected with the weighted model. All the computational results confirm its capability for community detection for the small or middle size networks.
基金supported by the Nature Science Foundation of China under Grand Nos. 70431002, 60874087, 60773120, and 10647001the Nature Science Foundation of Beijing under Grand No. 4092040
文摘Generalized Farey tree network （GFTN） and generalized Farey organized pyramid network （CFOPN） model are proposed, and their topological characteristics are studied by both theoretical analysis and numerical simulations, which are in good accordance with each other. Then weighted GFTN is studied using cumulative distributions of its Farey number value, edge weight, and node strength. These results maybe helpful for future theoretical development of hybrid models.
