论文标题
用于动态PU信号的能量检测的盲信号分离算法
A Blind Signal Separation Algorithm for Energy Detection of Dynamic PU Signals
论文作者
论文摘要
在动态初级用户（PU）场景中启用机会频谱访问的能量检测过程，其中PU在随机时间实例中从活动状态从活动状态变为无活性，需要估计几个参数，从噪声方差和信号到噪声比率（SNR）到瞬时和平均PU活动。参数估计的先决条件是在接收的信号时间范围内准确提取信号和噪声样本。在这封信中，我们提出了与众所周知的方法相比，低复杂性和准确的信号分离算法，这也对PU活性分布视而不见。在半实验模拟设置中分析了所提出的算法，以识别信号和噪声样本的准确性和时间复杂性，以及在PU信号的不同占用和SNR下，其在通道占用估计中的使用。结果证实了其适合获取有关PU动态行为的必要信息的适用性，否则这些信息在文献中被认为是已知的。
Energy detection process for enabling opportunistic spectrum access in dynamic primary user (PU) scenarios, where PU changes state from active to inactive at random time instances, requires estimation of several parameters ranging from noise variance and signal-to-noise ratio (SNR) to instantaneous and average PU activity. A prerequisite to parameter estimation is an accurate extraction of the signal and noise samples in a received signal time frame. In this letter, we propose a low-complexity and accurate signal separation algorithm as compared to well-known methods, which is also blind to the PU activity distribution. The proposed algorithm is analyzed in a semi-experimental simulation setup for its accuracy and time complexity in recognizing signal and noise samples, and its use in channel occupancy estimation, under varying occupancy and SNR of the PU signal. The results confirm its suitability for acquiring the necessary information on the dynamic behavior of PU, which is otherwise assumed to be known in the literature.
