滤波器组的多滤波器联合能量频谱感知算法

针对认知无线电系统,设计了一种基于滤波器组的多滤波器联合能量频谱感知算法.分析了算法的基本原理,给出了算法的流程,并以信噪比为参数说明了算法的优越性.仿真验证算法的检测概率与漏失概率,并对经典滤波器组的能量频谱感知算法的检测概率与漏失概率进行了比较,结果表明:本算法性能优于经典滤波器组能量频谱感知算法的性能.     

认知无线电中频谱感知技术

固定频谱分配政策导致频谱使用率低下,为克服这一缺点,人们提出使用认知无线电技术实现动态频谱接入,从而有效利用频谱空穴。频谱感知是认知无线电的关键技术。文中介绍了目前已提出的频谱感知技术:发射机检测(包括匹配滤波器检测、能量检测和周期平稳特征检测)、合作检测、接收机检测及基于干扰温度的检测,仿真分析了各种方法的优缺点及有待解决的问题。为满足多用户环境和实时性要求,仍需探讨新的频谱感知方法,提高检测性能。     

认知无线电中的宽频段频谱感知器设计

无线频谱感知器是认知无线电系统的核心。文章针对认知无线电中的宽频段频谱感知问题,提出了利用谐波滤波器组周期性检测的方案,并给出了基于能量检测的硬件实现框图。理论与仿真分析表明,基于快速傅里叶变换的周期图法不满足一致性估计条件,方差性能很难满足实际应用需求;分段平均周期图法与加窗平均周期图法收敛性好,方差小,但是功率谱密度主瓣较宽,分辨率低;多窗谱估计法具有较小的估计偏差,且其方差性能和频谱分辨率均远远优于周期图法,因而比较适合应用在实际的认知无线电系统中。     

基于能量检测的频谱感知方法研究

认知无线电是一种用于提高无线通信频谱利用率的新的智能技术,检测频谱空穴是否存在是实现认知无线电的前提和关键技术之一.首先简述认知无线电的背景和概念,针对认知无线电的频谱感知功能,介绍了基于能量检测的频谱检测方法,并在Matlab环境下进行了仿真实验,比较在相同的虚警概率情况下的检测概率与信噪比的关系.仿真实验结果表明,在相同的虚警概率时,当信噪比大的时候,检测概率越大.     

认知无线电中频谱检测的现状分析

认知无线电是一种用于提高无线电通信频谱利用率的新的智能技术。文章简述了认知无线电的背景和概念，针对认知无线电的频谱感知能力，详细对比分析了四种频谱检测技术：匹配滤波器法、能量检测法、循环平稳特性检测法和基于干扰的检测法，在此基础上分析了当前频谱检测技术所面临的挑战。最后探讨了干扰温度模型，并展望了频谱检测技术的发展前景。     

瑞利信道中自适应双门限频谱感知算法研究

频谱感知是认知无线电中的一项关键技术,能量检测、匹配滤波器检测和周期循环频谱检测是认知无线电中频谱感知技术中传统、经典的算法.基于能量检测的频谱感知算法因实现简单且不需要先验信息而被广泛应用,但低信噪比的情况下检测概率会降低,用户的检测性能不足,从而导致认知用户和主用户之间的冲突碰撞次数增多.针对以上存在的问题,在基于自适应频谱感知的基础上,利用噪声功率估计,提出了一种瑞利信道下的自适应双门限频谱感知算法.仿真结果表明,在低信噪比噪声不确定的情况下,这种算法能够大大提高检测概率,有效降低了认知用户和主用户之间的冲突碰撞次数,从而提高频谱的利用率.     

频率分析：基于滤波器组和门限倒谱的认知无线电频谱检测

频谱感知在认知无线电中占有重要的地位。其中,非参数的频谱检测被认为是认知无线电频谱感知的一个可行的候选方案。诸如Thomson多抽头频谱检测法等的基于滤波器组的改进周期图检测法能够取得很好的频谱动态感知范围,但是检测的方差却很大。最近,门限倒谱被用于降低周期图检测法的方差。本文把上述两者进行结合,从而能够在满足一定的频谱动态感知范围的情况下降低检测的方差。     

一种新型的认知无线电频谱空穴自适应检测算法

根据认知无线电实际频谱需求,通过对弱信号检测技术的研究,该文首次在认知无线电领域提出了一种基于三重矩阵累积估计的频谱空穴检测算法,该算法将频域块自适应滤波与矩阵重构、累积估计和频域平滑相结合实现弱信号检测。最后以QPSK调制信号为例进行了算法的计算机仿真,给出了性能分析。仿真结果表明该检测算法能够快速有效地实现弱信号检测并具有较高的检测概率,完全可以应用于认知无线电的频谱空穴检测。     

认知无线电的频谱感知技术研究

认知无线电是一种用于提高无线电通信频谱利用率的新的智能技术。论文首先简述了认知无线电的背景和概念;然后针对认知无线电感知频谱环境的功能,详细地对比分析了三种频谱检测的方法:匹配滤波器法、能量检测法和循环平稳特性检测法;最后介绍了“协同机制”用于改善极弱信号的接收问题。     

一种新的认知无线电频谱感知方法

认知无线电是一种用于提高无线电通信频谱利用率的新的智能技术。首先简述了认知无线电的背景和概念,然后针对认知无线电频谱感知的能力,对比分析了现有的三种频谱检测方法：匹配滤波器法、能量检查法和循环平稳特征检测法,在对其进行研究的基础上,提出一种将能量检测法和循环平稳特征检测法相结合的双门限检测法,通过仿真验证了该方法的有效性和优越性。     

Filter Bank Spectrum Sensing for Cognitive Radios

The primary task in any cognitive radio (CR) network is to dynamically explore the radio spectrum and reliably determine portion(s) of the frequency band that may be used for the communication link(s). Accordingly, each CR node in the network has to be equipped with a spectrum analyzer. In this paper, we propose filter banks as a tool for spectrum sensing in CR systems. Various choices of filter banks are suggested and their performance are evaluated theoretically and through numerical examples. Moreover, the proposed spectrum analyzer is contrasted with the Thomson's multitaper (MT) method - a method that in the recent literature has been recognized as the best choice for spectrum sensing in CR systems. A novel derivation of the MT method that facilitates our comparisons as well as reveals an important aspect of the MT method that has been less emphasized in the recent literature is also presented.     

一种新的联合频谱能量检测方法

认知无线电技术被认为是解决未来频谱资源紧张的一种有效方法。而频谱感知技术是认知无线电中的一种关键技术,只有通过有效的频谱感知才能合理利用空间的频谱空洞。在传统的时域能量检测的基础上给出了一种结合时域与频域的新的频谱感知方法。该方法充分利用了时域与频域能量检测的优点,理论分析与仿真结果表明,该方法具有感知准确率高,功耗小的优点。适合于未来认知无线电中的应用。     

基于ESD测试的无线电网络抗SSDF攻击协作频谱感知方案

针对认知无线电网络中协作频谱感知容易遭受数据伪造攻击的问题,提出一种基于检验统计和极端学生化偏差检验法的协作频谱感知方案。首先,将差分进化算法与加权增益合并软决策融合方法相结合,形成一种高效的节点决策融合机制。然后,在协作感知中,根据节点的软决策数据,利用检验统计消除故障认知节点。最后,利用提出的改进型ESD检验法消除恶意认知节点,从而形成全局决策。仿真结果表明,该方案在协作感知中能够有效过滤SSDF攻击数据,具有较低的误检测率。     

Analysis and Optimization of Sensing Reliability for Relay-Based Dual-Stage Collaborative Spectrum Sensing in Cognitive Radio Networks

Aiming at multiuser cognitive radio networks in a harsh electromagnetic environment, cooperative spectrum sensing with single cooperation can hardly achieve to the desired detection performance. In this paper, a relay-based dual-stage collaborative spectrum sensing model (DCSS) that combines the distributed method with the centralized method is proposed. Furthermore, the optimality of the detection performance of DCSS is investigated in an efficient and feasible way. The optimal voting rule value and the optimal energy detection threshold are also derived by minimizing the detection error rate of the entire network. Finally, an efficient fast sensing algorithm for a large-scale cognitive radio network is deduced, which requires the minimal number, and not all, of cognitive radio users for DCSS while satisfying the target detection error rate bound. The simulated results indicate that when compared to the normal single cooperation method, the optimized DCSS method can reduce the number of cognitive radio user by 65 % while still meeting the detection error rate requirement of less than 1 %.     

Polyphase filter bank based multi‐band spectrum sensing in cognitive radio systems

Spectrum sensing has been identified as an essential enabling functionality for cognitive radio (CR) systems to guarantee that CR users could share the spectrum resource with licensed users on a non‐interfering basis. Recently, simultaneous sensing of multi‐band licensed user activity has been attracting more and more research interest. Generally, the multi‐band sensing is implemented through energy detection by estimating power spectral density. In this paper, we investigate a multi‐band energy detection architecture based on different polyphase filter banks (PFBs), which aim to reliably sense multiple active bands by exploiting the low power leakage property of PFB. We have theoretically derived the closed‐form expressions of detection probability and false alarm probability for PFBs and fast Fourier transform based detectors, respectively. Theoretical detection thresholds are therefore computed, which ensures a fair comparison for different detectors. Final experimental results are presented to verify our theoretical analysis and demonstrate that PFBs based sensing architecture exhibits better sensing performance than the conventional FFT.Copyright © 2014 John Wiley & Sons, Ltd.     

随机共振在认知无线电频谱感知中应用的最新研究进展

频谱感知是认知无线电网络的一项关键技术.低信噪比(SNR)环境下频谱检测的性能会大幅降低,而随机共振(SR)能有效提高信号信噪比,所以将其应用到频谱感知中,能增强认知用户对主用户(PU)的检测性能.首先介绍了随机共振在认知无线电频谱感知中应用的最新研究进展,包括随机共振在本地感知中(如能量检测、协方差矩阵频谱感知、循环平稳特征检测)及协作感知中的应用,然后指出了随机共振在认知无线电频谱感知中还有待解决的问题,并提出了下一步的研究方向.     

基于证据折扣优化DSmT的协同频谱感知器

协同频谱感知器通过充分利用多个认知无线电用户的空间分集增益,对抗单用户深度衰落和阴影效应问题,降低了感知系统对本地感知用户的灵敏度要求,减少由于单用户检测不确定性带来的系统误判。利用D-S方法进行协同频谱感知,通过在本地提取置信指派,再上传至融合中心进行证据推理与判决,占用较窄的控制信道带宽,达到优于传统方法的检测性能,如“或”、“与”和“最优融合”感知方法。但低信噪用户带来的冲突数据会限制D-S方法性能,使其信噪鲁棒性较差。本文首先定义感知用户基本置信指派函数,基于DSmT提出证据折扣优化 DSmT协同频谱感知器。该感知器根据不同认知用户数据的可靠性,对其置信指派函数进行折扣,加强高可靠性数据对融合结果的贡献,降低不可靠数据对融合结果的干扰,有效解决冲突数据下的协同频谱感知信息融合问题。仿真结果表明,证据折扣优化DSmT协同频谱感知器具有良好的检测性能和信噪比鲁棒性。      

一种基于随机共振增强的协方差矩阵频谱感知算法

为了在避免对主用户系统产生有害干扰的同时 提高频谱利用效率,要求认知无线电系统的频谱感知算法能在极低的信噪比下快速检测出主用户信号。由于可以避免能量检测面临的噪声不确定性问题,基于协方差矩阵的检测算法是一种有效的盲频谱感知算法。为了进一步提高极低信噪比下的性能,本文提出了一种基于随机共振的协方差矩阵频谱感知算法。该算法通过在接收信号中加入优化的特定信号,利用随机共振原理,增大有无主用户信号下的检测统计量概率分布函数的分离度,提高频谱感知的性能。仿真结果表明,相对于现有的协方差矩阵频谱感知算法 ,在相同的虚警概率下,所提算法可以显著提高极低信噪比下的检测概率,同时大幅度缩减检测时间。      

Effective autocorrelation-based spectrum sensing technique for cognitive radio network applications

Spectrum sensing based on detection techniques enables cognitive radio networks to detect vacant frequency bands. The spectrum sensing gives the opportunity to increase the radio spectrum channels re-utilization. However, the main challenge in spectrum sensing is the simplicity of the considered detection approach and the amount of prior information needed to make an accurate decision. This paper proposes a novel sensing technique based on the autocorrelation function. This novel approach is based on the speed of convergence to zero of all autocorrelation coefficients. This technique shows the highest probability of detection for the same probability of false alarm target at low signal-to-noise ratio (SNR) compared with many standard detection techniques. The proposed method has been implemented using GNU Radio software and SDR (software-defined radio) platforms. The experimental results show the effectiveness of the proposed method under real scenarios.