Space alignment based on regularized inversion precoding in cognitive transmission

Rugui Yao, Geng Li, Juan Xu, Ling Wang, Zhaolin Zhang

科研成果: 期刊稿件文章同行评审

3 引用 (Scopus)

摘要

For a two-tier Multiple-Input Multiple-Output (MIMO) cognitive network with common receiver, the precoding matrix has a compact relationship with the capacity performance in the unlicensed secondary system. To increase the capacity of secondary system, an improved precoder based on the idea of regularized inversion for secondary transmitter is proposed. An iterative space alignment algorithm is also presented to ensure the Quality of Service (QoS) for primary system. The simulations reveal that, on the premise of achieving QoS for primary system, our proposed algorithm can get larger capacity in secondary system at low Signal-to-Noise Ratio (SNR), which proves the effectiveness of the algorithm.

源语言英语
页(从-至)824-829
页数6
期刊Radioengineering
24
3
DOI
出版状态已出版 - 2015

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