一种基于聚类的迭代多主用户定位算法

Xing Zhiqiang, Li Wei, Han Qiang
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引用次数: 1

摘要

在认知无线电环境中,多个同信道主用户同时存在是非常常见的。认知无线电通过了解pu的位置信息,可以更有效地利用频谱接入机会,提供更多的增值服务。提出了一种新的多pu定位算法,该算法通过k均值聚类和迭代运算寻找非合作pu的位置。仿真结果表明,该方法比传统的期望最大化(EM)算法具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An iterative multiple primary users localization algorithm based on clustering
Multiple co-channel primary users (PU) existing simultaneously is very common in cognitive radio environments. With the knowledge of the location information of PUs, the cognitive radio can use spectrum-access opportunities more effectively and provides more value-added services. A novel multiple PUs localization algorithm was proposed, which seeks non-cooperative PUs' position by executing k-mean clustering and iterative operations. Simulation results show that the proposed method achieves better performance than traditional expectation-maximization(EM) algorithm.
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