基于小波降噪的压缩感知—循环平稳检测技术

认知无线电技术通过次级用户动态接入空闲频谱来提高空闲频谱资源的利用效率,是认知无线电的重要环节。在低信噪比环境下,如何快速精确地进行频谱感知是频谱感知面临的重大挑战。提出了一种基于小波降噪的压缩感知—循环平稳特征检测器来实现低信噪比环境下的频谱检测。采用压缩感知技术提高了频谱感知的效率,并进一步利用小波变换技术降低了压缩感知过程中引入的压缩噪声,提高了低信噪比环境下的频谱感知准确度。仿真结果证明,提出的基于小波降噪的压缩感知技术能够实现低信噪比环境下的频谱空洞检测。     

SNR wall and cooperative spectrum sensing in cognitive radio under noise uncertainty

Cooperative energy spectrum sensing has been proved effective to detect the spectrum holes in Cognitive Radio (CR). However, its performance may suffer from the noise uncertainty, which is portrayed by the SNR wall in some literatures. In this paper we analyze the spectrum sensing performance under noise uncertainty and find an alternative approach to obtain the SNR wall. Then the average SNR wall is proposed to illustrate the statistically average impact of noise uncertainty. In addition, the cooperative sensing performance under noise uncertainty with AND rule is discussed. Analyses and numerical results show that cooperative sensing can significantly improve the sensing performance under the condition of noise uncertainty.     

基于功率谱分段对消频谱感知算法研究及性能分析

在实用的认知无线电系统中,频谱感知技术必须具备在噪声电平高动态变化和无线信道严重衰落电磁背景下,进行实时盲频谱感知的能力,这为经典的频谱感知算法带来巨大的挑战。该文提出的功率谱分段对消频谱感知算法,依据傅里叶变换的渐进正态性和相互独立性,计算出功率谱的统计特性,利用监测频带内部分谱线强度和与全部谱线强度和的比值作为检验统计量进行信号存在性的判断。该文推导了算法的虚警概率和不同信道模型下正确检测概率的数学表达式,并依据Neyman-Pearson准则得到判决门限的闭式表达式。理论分析和仿真结果均表明:功率谱分段对消频谱感知算法对噪声不确定度具有鲁棒性;固定信噪比,算法的频谱感知性能不受噪声电平改变的影响;应用于高斯白噪声和平坦慢衰落信道中,可在较宽的信噪比范围内获得较优越的频谱感知性能;算法计算复杂度低,可在微秒级时长内完成频谱感知。     

Maritime cognitive radio spectrum sensing based on multi-antenna cyclostationary feature detection

ABSTRACT

With the development of the maritime transportation industry, the number of ships is increasing and the ships are becoming more intelligent. Due to the rapid development of maritime communication, the demand for communication spectrum is increasing. Therefore, the maritime cognitive radio (CR) system is an effective solution. Because of the multipath fading caused by sea surface and atmosphere has a more serious influence on communication signals, which increases the instability of the signal reception, the spectrum sensing technology in maritime cognitive radio is more challenging than the spectrum sensing on land. In order to solve this problem, a cyclostationary detection algorithm for multiple antennas in fading model is proposed. A maximum ratio combining algorithm based on optimal weight correlation value (OWCV-MRC) is proposed for the diversity gain and system performance degradation caused by diversity technology on multipath fading channels. The algorithm uses the correlation values of the attenuation gains on the two different branches as the weighting coefficients of each branch, thus improving the coefficient matrix in the maximum ratio combining (MRC) algorithm. The simulation results show that the proposed algorithm can effectively detect the target signal in the fading channel with ultra-low signal to noise ratio (SNR).     

基于信噪比墙的协作能量检测算法

认知无线电技术可有效地检测到授权频段的频谱空洞,从而提高频谱效率.能量检测由于不需要授权用户的先验信息而被广泛应用.然而由于接收的噪声存在不确定性,使得在信噪比低于某一闸值时,无论观测时间多长,都无法保证检测结果满足要求的检测性能,这一闸值被称作“信噪比墙”.本文通过信噪比墙这一现象进行分析,同时由于协作感知算法在确定噪声下在提高检测性能方便表现出的优势,提出一种基于信噪比墙的协作能量检测算法,通过仿真结果分析,表明本文算法在检测性能和节能上较已有的协作算法具有优势.     

低信噪比下频率编码信号参数估计

针对低信噪比条件下,频率编码信号的瞬时频率估计容易受噪声影响的问题,提出了将自适应阈值消噪技术与小波变换结合起来的新方法。首先利用连续小波变换计算信号的小波谱,然后对小波谱进行自适应阈值消噪处理,进而提取小波谱脊线,得到频率编码信号的脉内调制信息。计算机仿真结果验证了该方法的可行性。     

基于信号集合势和连续性的认知无线电宽带频谱感知

针对传统感知算法依赖主用户信号与噪声先验信息,以及易受噪声功率估计不确定性影响的缺点,提出了一种基于信号集合势和连续性的宽带频谱感知方案。该方案将宽带频谱感知分为主用户占子带集合势的估计和子带位置判决两步。在两次不同感知结果中利用主用户连续占用子带的特性,有效地实现最终感知性能的提升。理论分析和仿真结果表明,该方案不仅能够解决传统感知方法依赖噪声和主用户信号先验信息的问题,而且对抗噪声功率不确定性具有鲁棒性。特别地,与传统的能量检测频谱感知算法相比,该算法能有效地实现宽带频谱盲感知。     

Fundamental Limitations on Pilot-based Spectrum Sensing at Very Low SNR

Spectrum sensing is one of the most challenging issues of Cognitive Radio communications. The possibility of extremely low signal-to-noise ratio (SNR) of the received signal poses a fundamental challenge to spectrum sensing. In this paper, pilot-based spectrum sensing for OFDM signals is investigated. It is shown that the existing pilot-based OFDM spectrum sensing algorithms suffer from the frequency offset between the transmitter and sensing devices, as well as the noise uncertainty in the sensing threshold design. We consequently propose a robust pilot-based spectrum sensing algorithm for low SNR OFDM signals using a sliding frequency correlator. The proposed algorithm processes additional bandwidth to eliminate the impact of frequency offset. In addition, considering the unknown noise statistics and its time-varying nature, a ratio threshold which is not sensitive to the noise power level is derived for spectrum sensing. Our theoretical analysis and simulation results show that this algorithm can achieve exceptionally good sensing performance at very low SNR, while being insensitive to time and frequency offsets and requiring no information of the noise statistics.     

Invariant wideband spectrum sensing under unknown variances

In this paper, we divide a wide frequency range into multiple subbands and in each subband detect whether in a primary user (PU) is active or not. We assume that PU signal at each subband and the additive noise are white zeromean independent Gaussian random processes with unknown variances. We also assume that at least a minimum given number of subbands is vacant of PU signal and propose an invariant Generalized Likelihood Ratio (GLR) detector. The concept of the grouping of subbands allows faster spectrum sensing of a subset of subbands which may be occupied by a specific PU. Also, we evaluate trade-offs involved in the proposed algorithms by simulation.     

奇异信号消噪中小波消失矩的选取

信号小波变换模的局部极大值和信号奇异性之间存在对应关系，利用信号和噪声小波变换模极大值在不同尺度上表现出的截然不同的性质，可以对奇异信号进行消噪。本文讨论了小波消失矩的阶数与信号Lipschitz指数间的关系，分析了消失矩对奇异信号检测的影响。实验结果表明，为了有效地检测奇异信号的各种奇异性特征，需要根据信号奇异性选择具有不同消失矩的小波。     

小波变换在心音奇异信号处理中的应用

针对如何剔除心音信号奇异点处的噪音信号的问题,该文利用小波变换方法,通过PhysioBank数据库中的相关数据,运用Matlab对含有噪音信号的心音奇异信号进行处理。其结果表明,该方法可在保留奇异信号的前提下,有效滤除噪音信号。说明利用小波变换技术分析与处理心音奇异信号是一种新的有效和实用的方法。     

基于拟合优度检测的子带频谱检测算法

根据雷达对抗侦察接收信号的特点,设计了基于动态非均匀信道化滤波的接收结构.重点研究了其中的频谱感知环节,提出了基于拟合优度检测的子带频谱检测算法.该算法首先假设至少含有K个子带不存在信号,再根据能量最小的K个子带输出估计噪声方差,用估计的噪声方差标准化各子带输出,从而将子带频谱检测问题转化为子带拟合优度的检测问题.该算法能够适用于噪声方差未知且无任何信号先验信息情况.理论分析和仿真实验证明了算法的有效性.     

干扰和噪声环境中直扩信号的截获

直扩（DS）信号功率谱密度（PSD）低，通常伴有干扰，因此在截获其中的信息时，需要把干扰也考虑在内，为此，提出了一种方法，充分利用直扩信号的特点和梳状滤波器的特殊频率响应特性，在小信噪比和小信干比的情况下有效截获直扩信号中的扩谱码，从而截获信息。     

子空间投影的频谱感知算法研究

为了发现空间中的“频谱空洞”而加以利用以使频谱利用率最大化,频谱感知技术得到了广泛关注。已有基于特征矢量的频谱感知算法因涉及大量特征值分解运算导致算法运算量大,不适应实时检测。本文提出的频谱感知算法利用信号子空间和噪声子空间之间的正交性,将次用户接收信号分别投影到上述子空间,根据投影值的差异实现快速频谱感知。理论分析和仿真结果表明本文提出的算法与已有算法相比有效降低了运算量,检测性能不受噪声不确定度影响、不需要预知主用户先验知识和噪声方差,且低信噪比、小采样情况下有更优越的检测性能。      

基于OMP算法的宽带频谱感知

频谱感知是认知无线电的一项关键技术,其能够检测出未被主用户占用的频谱空穴供次用户接入使用,提高频谱利用率.宽带频谱感知要求对数GHz 的带宽进行检测,过高的采样速率、大的数据量对现有的硬件设备提出了巨大的挑战.本文利用宽带频谱的稀疏性提出一种基于OMP算法的宽带频谱感知方法.该方法利用MWC采样实现对宽带模拟信号直接压缩采样;利用自相关矩阵对称分解特性和主用户信号独立性,得到有限维压缩采样信号模型,利用AIC/MDL准则估计稀疏度作为OMP算法迭代停止的条件,大大减少了算法复杂度;该方法不需要重构接收信号的PSD,直接在时域根据低速率采样信号,检测被占用信道.仿真结果表明,当带内信噪比大于9dB时,频谱检测概率高于90％.     

Minimum selection GSC in independent Rayleigh fading

We analyze the error performance of minimum selection generalized selection combining (MS-GSC), in which the minimum number of diversity branches are selected such that their combined signal-to-noise ratio (SNR) is above a given threshold. A flat Rayleigh fading channel with independent and distinctly distributed branch SNRs is considered. By transforming the ordered instantaneous branch SNRs to their differences, we derive the distribution of the number of selected branches in closed form. We then modify the derivation of this distribution to get the characteristic function (cf.) of the combiner output SNR. This cf. is used to obtain the symbol error probability for different coherent digital modulation schemes.     

基于小波变换的MSK信号码速率盲估计

针对最小频移键控调制信号的码速率估计问题,提出一种基于Haar小波变换的MSK信号码速率盲估计方法。首先对接收信号作傅里叶变换得到信号频谱,对频谱频点分析粗估计信号的码速率,接着通过粗估计的码速率选取短时傅里叶变换窗函数长度和3个小波尺度,利用短时傅里叶变换得到信号瞬时频率变化,再利用小波的边缘检测特性对信号瞬时频率序列相位跳变点检测,最后对检测结果作频谱分析,估计频率得到MSK信号的码速率。仿真结果表明,高于信噪比门限时本算法可以对MSK信号码速率有效估计。     

一种小波核函数的支持向量回归算法及应用

借助谐波小波函数在分析窄带信号方面的性能,利用支持向量回归算法,提出了一种基于谐波小波核函数和支持向量机相结合的谐波小波核支持向量回归算法,实现了小样本情况下微弱信号的精确检测.仿真和实测检测噪声数据的分析表明该算法可以有效地检测出舰船噪声中的线谱信号.     

宽带数据采集系统的相位噪声分析

研究了宽带数据采集系统的相位噪声、信号频率和信噪比之间的关系。根据相位噪声的计算模型,推导出多载频信号和宽带信号相位抖动信噪比的计算方法,通过噪声的频谱可以看出,独立时钟相位的抖动噪声是均匀分布在整个采样频谱中的,过采样和滤波可有效改善其信噪比。理论结果表明线性调频信号的相位噪声可用宽带信号的模型计算,当信号的带宽较小时,完全可由单频信号的计算公式得出近似的结果。最后,仿真结果验证了该SNR算法的有效性。