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基于干扰对齐的认知无线电网络中用户性能的优化设计

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Date of Publication:2022-10-10

Journal:信号处理

Issue:3

Page Number:422-429

ISSN No.:1003-0530

Abstract:Interference alignment (IA) is a promising interference management technology,which is widely used in cognitive radio (CR) networks,in order to eliminate the interference from cognitive users (CU) to authorized users (AU).However,IA will cause the decrease in the received signal-to-interference-plus-noise ratio (SINR) of AU,which affects its transmission rate.Especially at low SNR,the performance of AU is not guaranteed.According to different scenarios,this paper innovatively proposed two algorithms to design precoders for AU to optimize its transmission rate,the proposed algorithms improve the performance of AU tremendously.Moreover,to improve the CUs' performance,this paper proposed an optimum scheme for CUs' decoding filters to maximize their transmission rates.The simulation results show that the AU's transmission rate can be improved through using the proposed two algorithms,while CUs' transmission rates are also guaranteed.

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