Indexed by:会议论文
Date of Publication:2013-12-09
Included Journals:EI、CPCI-S、Scopus
Page Number:998-1002
Abstract:Interference alignment (IA) is a promising technique that can eliminate the interferences in wireless networks effectively, and has been applied to cognitive radio (CR). However, the quality of desired signal may be poor when the interferences are aligned in the direction similar to that of the desired signal. Thus, we propose a novel IA scheme based on antenna selection to improve the performance of CR networks. In the proposed scheme, multiple antennas are equipped at each secondary receiver, and we choose some of them that have the optimal channel coefficients according to a certain objective function. Furthermore, we also consider the condition of imperfect channel state information (CSI), and an efficient antenna selection IA algorithm based on discrete stochastic optimization is proposed. Simulation results show that the proposed schemes can improve the performance of IA-based CR networks significantly.
Associate Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates
Gender:Male
Alma Mater:大连理工大学
Degree:Doctoral Degree
School/Department:信息与通信工程学院
Business Address:创新园大厦B409
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