摘要
干扰温度是认知无线电领域中引入的一种衡量频段上干扰强度的量。本文提出了基于小波变换和干扰温度估计的频谱感知策略。该思想首先利用小波变换分析无线宽带系统中信号功率谱密度变化的奇异点,将整个宽带频谱分为几个子区域,实现对无线传播环境的"粗感知";再运用多窗谱估计与奇异值分解(MTM-SVD)算法进行处理,获得每个子区域的干扰温度值;最后与干扰温度门限比较判决,从而得到适合认知无线电系统应用的频谱空洞,完成对无线传播环境的"细感知"。
Interference temperature is used for weighing intensity of interference within some bands. This paper proposes one method for spectrum sensing based on wavelet transformation and interference temperature estimation. The method divides two steps. First, it analyses the singularity of power spectral densities over a wide frequency using wavelet transformation. The signal spectrum is decomposed into elementary building blocks of subbands that are well characterized by local irregularities in frequency. The step is called coarse sensing. Second, it computes the interference temperature value of each subband integrating multitaper method with singular value decomposition to compare these values with threshold. The second step is also called fine sensing.
出处
《电路与系统学报》
CSCD
北大核心
2009年第6期71-74,70,共5页
Journal of Circuits and Systems
基金
安徽省自然科学基金资助课题(050420101)
关键词
认知无线电
干扰温度
小波变换
多窗谱估计
奇异值分解
cognitive radio
interference temperature
wavelet transformation
multitaper method
singular value decomposition