Proposed Approaches for Cooperative Cognitive Radio

This paper in this topic concentrates on an important part is spectrum sensing (SS). It can detect the idle hole in spectrum by detection methods. This paper uses the sensing technique is called energy detector(ED). The ED depends on only the energy of the signal without other needs such as the modulation of signal or pre-knowledge about the signal and this is considered as advantage. This research proposed new two techniques are the additive wavelet transform (AWT) with Homomorphic Way (HW) and Haar Discrete Wavelet Transform (HDWT) approach. We apply these techniques are applied in wide band wireless signal by using the Cognitive Radio (CR) network. Each technique reduces the noise of signal before enter to the detection method ED. The HW is considered new technique in the wireless communication. This study will have these techniques as hybrid with the ED to increase the throughput for the cognitive user with a sufficient protection to the PU transmission. Also, it improves the probability of detection and reduces the probability of false alarm and the probability of error. The cooperative CR is used in this work which more than the non-cooperative cognitive user to detect the holes. The final decision for detection built on four fusion rules are the logic OR, logic AND, MAJORITY and K-Out-Of-M fusion rule. The two proposed are applied techniques on four fusion rule at constant sensing time. Then; study the four metric detection performances for each fusion rule by using the Additive White Gaussian Noise (AWGN) channel. At the end, comparison between two these proposed techniques with each fusion rule. Simulation results prove that the proposed scenario increases the probability of detection in the range of SNR of the PU from ?20 to ?5 dB using the theses proposed approaches.

     

基于信号采样自相关的步进宽带频谱感知方法

采用步进频域能量检测法可以提高在软件无线电平台的频谱感知的带宽范围,但能量检测法易受噪声不确定性的影响,而信号采样自相关检测法对噪声不确定性有很好的鲁棒性。为进一步提高软件无线电的检测性能,提出了基于信号采样自相关的步进宽带频谱感知方法。首先阐述了信号采样自相关检测的原理,然后对基于该原理的步进宽带检测方法的流程进行了分析,最后利用MATLAB软件仿真其检测性能。仿真结果表明,在信噪比（Signal-noise-ratio, SNR）不同的情况下,基于信号采样自相关的步进宽带频谱检测方法能达到所要求的检测性能。此 外,为了兼顾频谱感知的检测速度和频带带宽分辨率之间的关系,进一步提出了在原本固定步进值的步进宽带信号采样自相关的频谱感知方法中采用可变步进值的两阶段检测方法,该方法可 以获得较高的频带带宽检测分辨率和较短的检测时间。     

Optimal MAC based cooperative spectrum sensing in cognitive radio networks

This paper considers a cognitive radio (CR) system in non-ideal fading wireless channels and pro-poses cooperative spectrum sensing schemes based on coherent multiple access channels (MAC),serving as an alternative way to improve the cooperative spectrum sensing performance and provide space diversity for spec-trum sensing.Sufficient statistics are transmitted using a common channel from the secondary users (SUs) to a fusion center (FC) where the global decision is obtained.The optimal scaling factors of the proposed schemes are obtained by maximizing the detection probability under a target false alarm probability and a transmit power constraint.Because the proposed optimal MAC scheme has high computational complexity,a sub-optimal solu-tion based on maximization of the deflection coefficient (DC) is also proposed.Simulation results show that the proposed algorithms can significantly improve the spectrum sensing performance and approach the detection baseline.     

基于随机矩阵最大特征值分布的频谱感知算法

现有频谱感知算法在低信噪比时检测性能较低且受虚警概率影响大,针对此问题,提出了一种基于wishart矩阵样本协方差矩阵最大特征值的分布特性的频谱感知算法。该算法利用最大特征值与几何平均特征值的比值,不需要主用户的先验知识,不敏感于噪声,对相关信号和独立同分布信号均具有较高的检测性能。仿真结果表明,所提算法受虚警概率的影响较小,检测性能高,并且在采样点数、协作用户数、信噪比及虚警概率较小的情况下,也能获得较好的检测性能。     

Soft decision cooperative spectrum sensing with noise uncertainty reduction

Cognitive radio (CR) is a potential strategy for opportunistic access of idle resources to solve the conflicts between spectrum scarcity and underutilization. Spectrum sensing (SS) constitutes the most critical part in CR systems since the CR needs to detect the presence of primary signals reliably and quickly. Energy detection (ED) based SS is considered as the most preferable SS technique due to its simplicity and applicability. However, it is influenced by the effect of noise uncertainty which highly degrades its sensing performance. Cooperative spectrum sensing (CSS) is also introduced to mitigate some sensing problems such as multipath fading, shadowing, and hidden node problems. In this paper, we propose an enhanced fusion center (FC) rule for soft decision CSS using ED, which highly alleviates the noise uncertainty effect and enhances the sensing performance of cognitive radio networks (CRNs). In the proposed fusion rule, to increase the probability of detection and decrease the probability of false alarm, two dynamic thresholds are utilized by the FC. These thresholds are toggled based on predicting the current activity of the primary user (PU), and their values are dynamically changed based on estimating the noise uncertainty factor of the collected energy measurements from the CRs. To effectively predict (estimate) the current PU activity (the noise uncertainty factor), simple successive averaging processes over the collected energy measurements (the estimated noise variances) are performed by the FC, respectively. Theoretical analysis is performed on the proposed fusion rule for soft decision CSS to evaluate its enhanced false alarm and detection probabilities using different data combining schemes. Performance evaluations are also investigated to confirm the theoretical claims and to prove the effectiveness of the proposed scheme over the conventional ED based soft decision CSS.     

An improved robust image-adaptive watermarking with two watermarks using statistical decoder

This paper presents an improved image-adaptive watermarking technique. Two image watermarks are embedded in the high entropy 8?×?8 blocks of the host image. DWT is applied on these blocks using the principle of sub band coding. This decomposes the high entropy blocks into four sub band coefficients, wherein the approximation and vertical frequency coefficients are modeled using Gaussian (or Normal) distribution. The two watermarks are inserted in the host image using Adjustable Strength Factor (ASF). It is calculated adaptively using the fourth statistical moment known as kurtosis. A limited side information is also transmitted along with the watermarked image. This side information consists of high entropy block positions and Gaussian distribution parameters. To extract both watermarks from the received watermarked image, the high entropy block positions sent in the side information help in applying DWT to calculate the approximation and vertical frequency coefficients. Gaussian (or Normal) distribution is similarly used for modeling and calculating the distribution parameters. This helps the Maximum Likelihood (ML) decoder to recover the watermarks successfully using a statistical approach. Two important contributions are presented in this paper. Firstly, adjustable kurtosis values are used which improves the capacity and robustness of the proposed technique. Secondly, the proposed work is implemented on medical applications and gives better performance as compared to the existing methods. Further, the efficiency of the proposed work is evaluated by better simulation results using PSNR, NCC, SSIM and GMSD under different attacks. The technique is highly robust as watermarks survive under different attacks. This increases security and ensures copyright protection.

     

基于最小特征值分布的频谱感知算法

现有的频谱感知算法中,能量检测容易实现,但检测性能依赖噪声功率。基于随机矩阵理论的频谱感知算法巧妙地规避了噪声不确定性对检测性能带来的影响,但大都采用的是最大特征值的近似分布规律,所得到阈值表达式的精度有待进一步提高。针对上述问题,通过利用随机矩阵理论的最新研究成果,提出一种基于接收信号样本协方差矩阵最小特征值分布的频谱感知算法。最小特征值的分布函数不基于渐近假设,更加符合实际的通信情境。推导所得的阈值表达式是虚警概率的函数,在小样本情况下,对它的有效性和优越性进行了分析与验证。根据单一变量原则,分别在低样本点、低协作用户数、低信噪比和低虚警概率条件下对提出算法与最大最小特征值算法的检测性能进行了仿真比较,检测概率最多可以提高0.2左右。结果表明,该算法能够显著改善系统的检测性能。     

A robust deconvolution scheme for fault detection and isolation of uncertain linear systems: an LMI approach

Optimal H_∞ deconvolution filter theory is exploited for the design of robust fault detection and isolation (FDI) units for uncertain polytopic linear systems. Such a filter is synthesized under frequency domain conditions which ensure guaranteed levels of disturbance attenuation, residual decoupling and deconvolution performance in prescribed frequency ranges. By means of the Projection Lemma, a quasi-convex formulation of the problem is obtained via LMIs. A FDI logic based on adaptive thresholds is also proposed for reducing the generation of false alarms. The effectiveness of the design technique is illustrated via a numerical example.     

A semi-blind HVS based image watermarking scheme using elliptic curve cryptography

In the present paper, an advanced encryption technique commonly known as Elliptic Curve Cryptography (ECC) is used to embed a binary image as a watermark in five grayscale host images in a semi-blind manner. The ECC algorithm is a fast encryption technique which successfully encrypts the subject with significantly less number of bits as compared to other popular encryption algorithms such as Rivest-Shamir-Adleman (RSA) and Direct Selling Association (DSA). In the proposed watermarking scheme, embedding in the grayscale host images is carried out in DWT-SVD domain. First, entropy based Human Visual System (HVS) parameters are computed block wise to identify the most appropriate blocks in spatial domain. First level DWT is computed for these selected blocks and watermark embedding is carried out by using the calculated Singular Value Decomposition (SVD) parameters. Preliminary results of this work show that proposed scheme outperforms the other similar schemes carried out in DCT-SVD domain without using any encryption method. It is concluded that the use of DWT-SVD hybrid architecture along with the fast encryption technique ECC is responsible for better performance in present case. In the second part of this simulation, an established HVS model working in DCT domain is implemented and compared with the entropy based HVS model implemented in transform domain to embed the ECC encrypted binary watermark in images. In this case also, proposed scheme performs better both in terms of visual imperceptibility and robustness as compared to other scheme. It is concluded that HVS parameters – Luminance, Contrast and Edge Sensitivity are better placed in comparison to entropy parameters to examine image features and characteristics for watermarking purpose.     

基于熵权法的CRSN软决策协作频谱感知方法

在实际的无线环境中,阴影和衰落的影响会导致传感节点接收到的信号具有不同的特征。因此,深度衰落中的一些协作节点会出现严重的漏检,这将影响融合操作的最终结果。针对上述问题,提出一种基于熵权法的认知无线传感网（cognitive radio sensor network,CRSN）软决策协作频谱感知方法。该方法将传感器节点组织成逻辑组,以获得能源效率和传感性能的提高,在接收到来自所有成员节点的软传感信息后,簇头采用等增益的软融合来进行簇间融合,然后将局部决策转发给融合中心,在最终决策过程中,采用熵权法为相应的聚类局部决策分配最优权值。仿真结果表明,该方法检测概率和总误差概率方面均优于典型的协作频谱感知分簇方案。     

非理想报告信道下协作频谱感知研究及性能分析

分析了理想报告信道下协作频谱感知性能,提出了基于改进的能量检测的协作频谱感知方案。改进的能量检测器通过对接收信号样本取任意正数p次方的和作为检测统计量,每一个认知用户将本地检测结果发送到数据融合中心,数据融合中心采用OR准则最终判断授权用户信号是否出现。针对非理想报告信道情况,推导了误检概率最小下参与协作的认知用户个数,并数值仿真得到了误检概率最小下的p值。数值仿真结果也表明协作频谱检测概率在低信噪比情况下随着p值的增大而提高。     

An analytical approach to the deployment quality of surveillance wireless sensor networks considering the effect of jammers and coverage holes

The requirements of surveillance wireless sensor networks, such as latency and reliability provisions, are directly related to the deployment quality, which is an indicator of the sensing capability of the network. The determination of the deployment quality is hindered by various factors that cause coverage holes, such as the existence of jammers and destruction of sensors. This paper presents an analytical deployment quality measure in terms of network parameters, including the sensor count, sensing coverage, coverage hole count, coverage hole area size and deployment area size. Assuming a random deployment model for both sensors and holes, our method determines the probability of detection of a target following a linear trajectory by a single sensor and generalizes it to derive the probability of detection in a network with coverage holes. The overall probability of detection is used as the network quality measure and is proposed as a suitable metric under sensor loss assumptions. The proposed deployment quality metric (DQM) is based on the shortest path strategy to provide a conservative estimation for the intruder detection performance. We show that it provides a good estimation of the actual deployment quality with given coverage hole and jamming area properties. Our metric is suitable for real life and simulation scenarios and is computationally inexpensive compared to both simulation based and distributed quality measurements.     

Perceptually adaptive spread transform image watermarking scheme using Hadamard transform

The present paper proposes a digital image watermarking scheme using the characteristics of the human visual system (HVS), spread transform technique and statistical information measure. Spread transform (ST) scheme is implemented using the transform coefficients of both the host and the watermark signal. Watermark embedding strength is adaptively adjusted using frequency sensitivity, luminance, contrast and entropy masking of HVS model. The choice of Hadamard transform as watermark embedding domain offers several advantages, such as low loss in image information (higher image fidelity), greater reliability of watermark detection and higher data hiding capacity at high degree of compression. Performance of the proposed method is compared with a number of recently reported watermarking schemes based on spread spectrum (SS) and quantization index modulation (QIM).     

认知无线电网络多用户智能协作频谱感知算法

认知无线电网络中,单用户频谱感知容易受到阴影效应、多径衰落及隐蔽终端等不利因素的影响,造成感知结果的误判.为了提高系统的检测性能,并减少感知花销,提出了多用户智能协作频谱感知算法.各个认知用户根据估计信噪比自适应选择不同的感知策略,当估计信噪比高于选择阈值时采用双门限能量感知,低于选择阈值时则采用循环平稳特征检测,并在同一个感知周期内只进行一种较优的感知策略,从而在不明显增加计算复杂度的情况下,克服了能量感知在低信噪比条件下鲁棒性差的缺点,实现了智能检测.仿真结果表明,智能协作频谱感知有效提高了系统检测概率,缩短了平均感知时间,有较好的鲁棒性.     

基于门限动态调整的最优协作检测方法

为提高协作频谱感知的检测效率、减少系统的反馈开销,提出一种基于门限动态调整的最优协作检测方法。在单节点检测错误概率最小的情况下,导出能量检测中门限值与信噪比的关系表达式,利用二分法求得不同信噪比下的动态门限值。根据系统恒虚警率和恒检测率计算最优协作用户数,并与动态门限值相结合得到系统检测错误概率。仿真结果表明,该方法协作检测概率较高,检测错误概率较低。     

一种时域—码域联合的认知无线电频谱感知算法

为了提高认知无线电系统中频谱感知的性能,对多维联合的频谱感知进行了研究,提出一种时域—码域联合的频谱感知算法。该算法主要利用了直接序列扩频主用户信号频谱空间中时域与码域的特性,分别从时域与码域的角度对信道的状态进行检测,其中时域采用能量感知,码域分析扩频主用户信号的二次功率谱,最终共同确认信道状态。仿真结果表明,联合感知算法对应的检测性能优于单纯时域或码域感知,能够直接应用于直接序列扩频主用户的频谱感知。     

协作频谱感知的系统效用优化分析

协作频谱感知可以提升认知无线电的频谱感知能力,但不同的系统参数对协作频谱感知系统的性能会产生不同的影响。在综合考虑系统资源利用率和归一化吞吐量的情况下,对不同条件下用户数和感知时长对系统性能的影响进行分析。并在检测概率约束条件下,对结合系统检测概率和归一化吞吐量的系统效用提出优化方法,可以求出满足条件的最大系统效用值。仿真结果表明,在不同的环境和条件限制下,达到最大系统效用所需要的用户数和感知时长也是不同的。     

基于改进型能量检测的加权协作频谱感知算法

针对单节点能量检测法存在的“隐藏终端”和检测准确性低以及协作频谱感知算法大多采用等权重进行数据融合,未考虑不同节点所处的通信环境对检测性能的影响等问题,提出一种基于改进型能量检测的自适应加权协作频谱感知算法。该算法通过对单节点能量检测方法的改进,在单节点检测错误概率最小的条件下,导出了信噪比与判决门限的关系式,利用二分法求得不同信噪比下的动态门限值,得到相应的虚警概率和检测概率,以虚警概率和检测概率的函数作为加权因子进行数据融合。仿真结果表明,所提算法使协作感知系统在低信噪比条件下也能获得可靠的检测性能。     

一类Markov跳变系统的综合时频分析模型切换检测

在Markov跳变系统的估计问题中,目前的多模型估计器采用模型概率检测模型切换;这是一种基于信号幅值的检测方法;事实上,模型切换表征了系统的暂态过程,因而系统某些特征的频谱特性在模型切换前后存在差异;因此提出一类Markov跳变系统的综合时频分析模型切换检测方案（ITFA）;同时给出统计意义下的模型检测评价指标;仿真结果表明：与标准的交互式多模型算法相比,ITFA方法具有检测概率高、延迟时间小的优点;同时,ITFA对于先验性的滑窗长度、检测阈值具有较好的鲁棒性.     

基于小波视觉模型的乘性水印算法

虽然小波域加性水印算法具有较好的不可感知性,但其鲁棒性较弱。因此,结合小波域视觉模型,提出了一种基于小波视觉模型的乘性图像水印算法。在水印嵌入过程中,为平衡水印的不可感知性和鲁棒性,以中频子带作为水印嵌入空间,并根据图像的频域敏感度、亮度敏感度、纹理复杂度确定水印的嵌入强度。在水印检测过程中,采用广义高斯分布(GGD)对小波系数的统计特性进行刻画,并通过奈曼-皮尔逊(NP)准则确定水印系统的检测阈值,给出了水印系统的虚警概率和检测概率之间的接收者操作特征(ROC)曲线关系。最后通过实验测试了该算法在抗压缩、叠加噪声、缩放和剪切等攻击时的鲁棒性能。仿真结果表明：该算法具有较好的检测性能以及在抗攻击时具有较强的鲁棒性。