Impact of noise estimation on energy detection and eigenvalue based spectrum sensing algorithms
Impact of noise estimation on energy detection and eigenvalue based spectrum sensing algorithms
复制标题
噪声估计对能量检测和基于特征值的频谱感知算法的影响
DOI：
10.1109/icc.2014.6883512
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
R. Garello
中科院分区：
文献类型：
--
作者：
P. Dhakal;D. Riviello;F. Penna;R. Garello
本文研究了在平坦衰落信道下的半盲频谱感知算法，即能量检测（艾德）和罗伊最大根检验（RLRT）。噪声方差的知识是必要的艾德和RLRT的最佳性能。然而，噪声方差的变化和不可预测性是不可避免的。为了科普噪声方差先验知识的缺乏，引入了辅助噪声方差估计的思想，从而为每种方法提出了一种混合的信号检测方法。推导了该方法的检测性能，并用封闭形式的解析表达式表示。噪声估计精度对艾德和RLRT的性能的影响进行了比较，在接收机工作特性（ROC）曲线和性能曲线（检测/误检概率作为SNR的函数，通过固定的虚警概率）。它的结论是最佳性能的艾德和RLRT可以实现，即使使用估计的噪声方差，通过使用大量的时隙方差估计。最后，还发现，由于噪声的不确定性的损害减少RLRT w。R. t. ED.
In this paper, semi-blind class of spectrum sensing algorithms, Energy Detection (ED) and Roy's Largest Root Test (RLRT), are considered under a typical flat fading channel scenario. The knowledge of the noise variance is imperative for the optimum performance of ED and RLRT. Unfortunately, the variation and unpredictability of noise variance is unavoidable. An idea of auxiliary noise variance estimation is introduced in order to cope with the absence of prior knowledge of the noise variance, thus a hybrid approach of signal detection is set forth for each considered method. The detection performance of the methods are derived and expressed by closed form analytical expressions. The impact of noise estimation accuracy on the the performance of ED and RLRT is compared in terms of Receiver Operating Characteristic (ROC) curves and performance curves (Probability of Detection/Miss-detection as a function of SNR by fixing the false alarm probability). It is concluded that optimum performance of ED and RLRT can be achieved even with the use of estimated noise variance by using a large number of slots for variance estimation. Finally, it is also found out that the impairment due to noise uncertainty is reduced on RLRT w. r. t. ED.