Accurate Estimation of Primary User Traffic Based on Periodic Spectrum Sensing

被引：0

作者：

Al-Tahmeesschi, Ahmed ^{[1
]}

Lopez-Benitez, Miguel ^{[1
]}

Lehtomaki, Jayne ^{[2
]}

Umebayashi, Kenta ^{[3
]}

机构：

[1] Univ Liverpool, Dept Elect Engn & Elect, Liverpool, Merseyside, England

[2] Univ Oulu, Ctr Wireless Commun, Oulu, Finland

[3] Tokyo Univ Agr & Technol, Grad Sch Engn, Fuchu, Tokyo, Japan

来源：

2018 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC) | 2018年

关键词：

Cognitive radio; spectrum sensing; primary activity statistics; COGNITIVE RADIO; ACCESS;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

An accurate estimation of the primary statistics is essential for Cognitive Radio (CR) systems. This knowledge can be exploited to enhance CR performance and reduce the interference with the primary users. In this work, we propose a method based on the Method of Moments (MoM) to improve the distribution estimation. A Modified Method of Moments (MMoM) with a correction factor is proposed to improve the estimation of moments and thus the resulting primary distribution. The simulation and experimental results show that the MMoM approach is notably more accurate. Finally, we study the importance of having a sufficiently large sample space and the effect of sample size on the moments and the primary distribution estimation.

引用

页数：6

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