The interference alignment （IA） algorithm based on FDPM subspace tracking （FDPM-ST IA） is proposed for MIMO cognitive network （CRN） with multiple primary users in this paper. The feasibility conditions of FDPM-S...The interference alignment （IA） algorithm based on FDPM subspace tracking （FDPM-ST IA） is proposed for MIMO cognitive network （CRN） with multiple primary users in this paper. The feasibility conditions of FDPM-ST IA is also got. Futherly, IA scheme of secondary network and IA scheme of primary network are given respectively without assuming a priori knowledge of interference covariance matrices. Moreover, the paper analyses the computational complexity of FDPM-ST IA. Simulation results and theoretical calculations show that the proposed algorithm can achieve higher sum rate with lower computational complexity.展开更多
A novel multiple PUs (Primary Users) localization algorithm was proposed, which estimates the number of PUs by SVD (Singular Value Decomposition) method and seeks non-cooperative PUs' position by executing k-mean ...A novel multiple PUs (Primary Users) localization algorithm was proposed, which estimates the number of PUs by SVD (Singular Value Decomposition) method and seeks non-cooperative PUs' position by executing k-mean clustering and iterative operations. The simulation results show that the proposed method can determined the number of PUs blindly and achieves better performance than traditional expectation-maximization (EM) algorithm.展开更多
基金the National Nature Science Foundation of China under Grant No.61271259 and 61301123,the Chongqing Nature Science Foundation under Grant No.CTSC2011jjA40006,and the Research Project of Chongqing Education Commission under Grant No.KJ120501 and KJ120502
文摘The interference alignment （IA） algorithm based on FDPM subspace tracking （FDPM-ST IA） is proposed for MIMO cognitive network （CRN） with multiple primary users in this paper. The feasibility conditions of FDPM-ST IA is also got. Futherly, IA scheme of secondary network and IA scheme of primary network are given respectively without assuming a priori knowledge of interference covariance matrices. Moreover, the paper analyses the computational complexity of FDPM-ST IA. Simulation results and theoretical calculations show that the proposed algorithm can achieve higher sum rate with lower computational complexity.
基金Sponsored by the Scientific Research Program of Beijing Municipal Commission of Education ( Grant No. KZ2010100009009)Funding Project for Academic Human Resources Development in Institutions of Higher Learning Under the Jurisdiction of Beijing Municipality ( Grant No. PHR201008186) Scientific Research Fund of Heilongjiang Provincial Education Department ( Grant No. 11541083)
文摘A novel multiple PUs (Primary Users) localization algorithm was proposed, which estimates the number of PUs by SVD (Singular Value Decomposition) method and seeks non-cooperative PUs' position by executing k-mean clustering and iterative operations. The simulation results show that the proposed method can determined the number of PUs blindly and achieves better performance than traditional expectation-maximization (EM) algorithm.
