基于频谱感知结果的认知无线电用户分簇方法

摘要

认知无线电用户的分簇由于不同位置频谱环境的巨大差异而成为亟待解决的问题之一.该文分析了认知无线电用户频谱感知结果之间相关性,基于分析结论提出一种基于频谱感知结果相关性的分簇算法,并考察了频谱感知结果量化对该算法的性能影响,得出增加频段数量的方式能够部分补偿量化带来的性能损失的结论.仿真显示,该文的分簇算法能够有效地对认知无线电用户进行分簇,在频谱感知结果量化的条件下,也能达到较好的分簇性能.从可靠性、准确性和自适应能力等方面,相较传统基于地理位置的分簇方法,该文所提出的分簇算法能综合考虑频谱环境的特点,更加具实用价值.%User clustering is one of the most important problems because of the difference of the frequency spectrum utilization situation from cognitive users. This paper gives the analysis result of correlation between cognitive radio users and also proposes the clustering algorithm based on this analysis. Considering the real situation, the effects of data quantization are derived and the derivation shows the performance loss could be compensated partly through the increase the number of spectrum bands. Finally, the simulation shows the proposal could perform well whether the data quantization is adopted or not. From the aspect of reliability, accuracy and adaptability, the proposed algorithm, which gives a comprehensive consideration of the spectrum environment and other factors, is more practical than the traditional clustering algorithm based on the geographic location.