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On the beamforming and blind interference threshold estimation in underlay cognitive system

机译:底层认知系统中的波束成形和盲干扰阈值估计

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This paper aims at providing a solution for blind interference threshold estimation in an underlay cognitive network. Unlike the traditional methods that mainly depend on pre-cooperation between primary and secondary users to settle on a predefined threshold. For threshold estimation, blind detection of modulation and signal-to-noise ratio (SNR) are used. For the sake of beamforming, several localization algorithms are compared to settle on best one for cognitive environment. Beamforming algorithms as Linear Constraint Minimum Variance and Minimum Variance Distortion less are compared. Just nulling the primary user after knowledge of its location is discussed against working under interference threshold.
机译:本文旨在为底层认知网络中的盲干扰阈值估计提供一种解决方案。与传统方法不同,传统方法主要依靠主要和次要用户之间的预先合作来确定预定义的阈值。对于阈值估计,使用了对调制和信噪比(SNR)的盲检测。为了进行波束成形,比较了几种定位算法,以针对认知环境确定最佳算法。比较了线性约束最小方差和最小方差较小的波束成形算法。讨论了主要用户的位置信息后,仅针对主要用户进行调零,以防止在干扰阈值下工作。

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