认知无线电中基于自相关矩阵的协作盲感知

为了克服传统的认知无线电频谱感知算法存在的不足,提出了一种基于自相关矩阵的协作式盲频谱感知方法,以提高频谱感知能力.该方法从样本自相关矩阵中提取检测统计量,采用双门限混合判决方法得到本地检测结果.认知基站将本地检测信息分成两类,并对软判决信息实施可靠性融合,最后给出全局判决结果.该方法是一种盲感知方法,不需要知道主用户...     

基于观测矩阵优化的自适应压缩频谱感知

推导了自适应压缩感知中的重构估算误差,研究了如何降低观测矩阵列向量之间的自相关性,分析了观测矩阵优化对压缩感知重构算法的影响。将观测矩阵优化与压缩感知自适应过程相结合,提出了基于观测矩阵优化的自适应压缩频谱感知算法。仿真结果证实,所提算法比传统算法重构时产生的均方误差(MSE)更低,在同一观测次数下检测概率更高,在达到同等接收操作性能(ROC)时所需观测次数更少。     

基于循环前缀频域自相关的OFDM信号频谱感知

针对无线通信频谱资源有限并且利用率非常低的问题,研究了认知无线电系统中基于信号典型特征的频谱感知策略,并进行动态频谱检测.提出了一种基于循环前缀频域自相关的频谱感知算法,利用正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)信号的循环前缀具有循环平稳特性,在信...     

一种基于PN累积自相关的DTMB频谱感知新算法

针对数字电视地面广播传输标准(DTMB)的频谱感知问题,提出了一种新的基于DTMB信号帧中伪随机(PN)序列累积自相关的频谱感知算法。所提算法的创新性在于通过联合多个不同相关间隔的累积自相关结果作为频谱感知的检验统计量,充分利用了有限频谱感知时间内的信号信息。仿真结果表明,当把感知时间设为50 ms时,为了确保频谱感知检测的虚警概率和漏验概率都低于0.01,针对DTMB信号的3种帧头模式,所提算法所需的信噪比分别为-20.5 dB、-21 dB和-22 dB,优于已有的频谱感知算法。此外,仿真结果还表明载波频偏和多径衰落对所提算法的性能几乎没有影响。     

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.     

基于特征值极限分布的合作频谱感知算法

采用最新的随机矩阵理论,对多个认知用户接收信号采样协方差矩阵的最小特征值的极限分布进行了分析,提出了一种改进的最大最小特征值合作感知和门限判决方法。该算法不需预知授权用户信号的先验知识,且能有效克服噪声不确定度的影响。与现有算法相比,在给定虚警概率时,仿真结果显示该算法判决门限更低、检测概率更高;而且在认知用户和采样数较少时,也能获得很好的检测性能。     

基于非参量累积和的合作频谱感知

针对认知无线电网络中频谱感知的检测时延降低问题,提出了基于非参量累积和的合作频谱感知算法。本地认知用户预处理频谱观测数据,获得观测数据相对于信念值的正向漂移和负向漂移。为了缩短检测延迟,认知用户只将数据的正向漂移同步传输至融合中心。融合中心融合正向漂移得到判决信息,采用非参量累积和算法依时间序列顺序累加判决信息,判断主用户是否正在使用授权频段。为了解决不传输负向漂移引起的虚警问题,改进算法提出融合中心可以保留首次判决,经过等待时间间隔后再作出最终判决。相对于传统的软融合算法,改进融合规则的合作频谱感知算法具有较低的检测延迟。     

利用秩和检验的多天线协作频谱感知

高效稳定的频谱感知是认知无线电系统的关键环节.传统的能量检测算法受噪声不确定性影响,而协方差矩阵类算法在天线相关性低时性能较差.针对上述缺陷,利用秩来衡量由信道衰落导致的同一感知时刻不同天线上的信号功率差异,提出通过构建秩和统计量来实现频谱感知的算法.另外,推导了所提算法判决门限的理论表达式,结果显示其不受采样点数影响,因此当采样点数变化时无需重新设置门限.理论分析和仿真表明所提算法不受噪声不确定度的影响,并且在低天线相关性时可以保持良好的性能.     

多输入多输出系统基于特征函数频谱盲检测

提出多输入多输出（Multiple-Input Multiple-Output,MIMO）认知无线电系统中基于多元特征函数的频谱盲检测方法.所提方法不需要知道授权用户传输信号的先验知识,也不需要知道信道噪声的方差.通过计算次用户多天线系统接收到的信号样本向量的经验特征函数,MIMO系统中的频谱检测就转换为多元特征函数检验问题.通过度量经验特征函数与已知特征函数的距离, 实现频谱检测.在MIMO系统中,基于特征函数的频谱检测算法比现存的频谱检测方法,具有更好的性能,特别是在低信噪比、小样本条件下.     

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.     

Cognitive wideband spectrum sensing using cosine-modulated filter banks

A multichannel joint spectrum sensing strategy based on cosine-modulated filter banks (CMFBs) was developed to improve sensing efficiency. The received wideband signal was split into several bands through the filters that are constructed by grouping continuous sub-band filters. Through flexibly designing prototype filter, not only the spectrum of non-uniform bandwidth can be estimated, but also the spectral leakage between adjacent channels can be adjusted. The probabilities of false alarm and detection for multichannel jointly spectrum sensing in the Rayleigh fading channel were deduced. The decision thresholds of different channels were obtained as regards the probability of false alarm. Simulation results show that compared with the traditional energy detector, the detection capability and sensing efficiency have been improved, especially at low signal-to-noise ratio. The CMFB-based multichannel joint sensing scheme not only increases the efficiency of detection, but also enhances the flexibility on the control of bandwidth and spectral leakage between neighbouring channels.     

认知无线电中基于感知信息量化的合作频谱感知

针对认知无线电频谱感知性能的提高与传输开销的矛盾,本文提出了一种基于感知信息量化的合作频谱感知方案。该方法对各认知用户的本地检测结果采用3个判决门限进行2比特位的量化,在融合中心处对量化信息加权处理后,得到最终主用户是否存在的判决。本文详细研究了采用该方案的检测概率,虚警概率和吞吐量,理论分析和仿真结果表明,该方法在每个认知用户只增加1bit传输开销的前提下能够极大的改善检测性能,实现了检测性能与传输开销的较好权衡。     

Optimization algorithm of periodical cooperative spectrum sensing in cognitive radio

To decrease the interference to the primary user (PU) and improve the detected performance of cognitive radio (CR), a single‐band sensing scheme wherein the CR periodically senses the PU by cooperative spectrum sensing is proposed in this paper. In this scheme, CR first senses and then transmits during each period, and after the presence of the PU is detected, CR has to vacate to search another idle channel. The joint optimization algorithm based on the double optimization is proposed to optimize the periodical cooperative spectrum sensing scheme. The maximal throughput and minimal search time can be respectively obtained through the joint optimization of the local sensing time and the number of the cooperative CRs. We also extend this scheme to the periodical wideband cooperative spectrum sensing, and the joint optimization algorithm of the numbers of the sensing time slots and cooperative CRs is also proposed to obtain the maximal throughput of CR. The simulation shows that the proposed algorithm has lower computational quantity, and compared with the previous algorithms, when SNR = 5 dB, the throughput and search time of the proposed algorithm can respectively improve 0.3 kB and decrease 0.4 s. The simulation also indicates that the wideband cooperative spectrum sensing can achieve higher throughput than the single‐band cooperative spectrum sensing. Copyright © 2012 John Wiley & Sons, Ltd.     

分集技术下频谱感知的性能分析

研究了在普适的相关非同分布Nakagami-m衰落模型情况下,次用户采用能量检测和等增益合并技术进行频谱感知的性能.给出了检测概率的闭式表达式,并通过分析漏检概率的渐进曲线斜率说明分集技术对频谱感知性能带来了提升.利用数值结果和Monte-Carlo仿真验证了理论推导的准确性.最后通过Monte-Carlo仿真观察了等增益合并分集技术下信道相关性对检测概率的影响.     

一种低速采样的协同宽带频谱感知方法

频谱感知是通信系统抗干扰和智能化的关键能力.针对认知无线电系统窄带频谱感知技术受制于数模转换器件的发展水平,难以解决认知无线电系统宽带、实时频谱感知的问题,提出一种多节点协作的认知无线电系统宽带频谱感知方法.该方法设计由多个认知节点对目标频段执行次奈奎斯特采样来降低采样速率,采用能量检测方式对采样矢量进行集中式融合判决,实现宽频段范围内干扰信号的谱定位和判断,降低各个感知节点的采样速率,支撑认知网络系统构建高实时、宽频带频谱感知的能力.计算机仿真试验结果表明,所提方法达到90％检测概率时压缩比要求为0.025,具有可靠性与有效性.     

Efficient secondary access with intelligent spectrum sensing in cognitive radio networks

In cognitive radio networks, cooperative sensing can significantly improve the performance in detection of a primary user via secondary users (SUs) sharing their detection results. However, a large number of cooperative SUs may induce great sensing delay, which degrades the performance of secondary transmissions. In this paper, we jointly consider cooperative sensing and cognitive transmission in cognitive radio networks, aiming to achieve efficient secondary access with low sensing overhead under both the sensing time and reporting power limitations, where primary users are guaranteed to be sufficiently protected. We first propose an adaptive sensing scheme to lower the detection time while not degrading the detection probability. Then, based on the proposed adaptive sensing scheme, an efficient cognitive transmission protocol is well designed, which improves the throughput of secondary transmissions while ensuring the QoS of primary transmissions. We analyze the performance for the proposed secondary access framework in terms of misdetection probability, average detection time and normalized secondary throughput, respectively, and derive their closed‐form expressions over Rayleigh fading channels with considering the reporting errors accordingly. We also study the problems of optimizing the number of cooperative SUs to minimize the misdetection probability and average detection time, and maximize the normalized secondary throughput for proposed framework. Simulation results reveal that the proposed framework outperforms the traditional case significantly. Copyright © 2013 John Wiley & Sons, Ltd.     

最优线性认知无线电协作频谱感知技术研究

频谱感知是检测频谱空穴,实现动态频谱接入的前提和关键。单认知用户检测存在阴影效应和多径衰落等影响,检测效果较差。多用户协作频谱感知是目前频谱感知的主要手段。文中针对常用的协作频谱感知方法的不足,提出一种基于最优线性加权的协作频谱感知方法,对其检测模型与检测算法进行分析,并进行仿真。仿真结果表明,最优线性加权协作频谱感知在相同的条件下相比常用协作频谱感知具有更大的检测概率,更优良的检测性能。     

A selective decision–fusion rule for cooperative spectrum sensing using energy detection

Increasing the number of terminals in a cognitive radio network is known to improve the accuracy of cooperative spectrum sensing at the cost of reducing the useful communication time. This downside can be partially mitigated using decision‐based fusion and/or sequential reporting. This paper proposes a novel selective decision‐based cooperative spectrum sensing strategy that limits the reporting time to a single reporting slot with a possibility for retransmissions using automatic repeat request. The terminal with the highest energy estimate sends its local decision to the fusion center to make a final decision. Potential decoding errors are mitigated using threshold‐based automatic repeat request. The performance of the proposed strategy is studied using rigorous mathematical analysis and intensive computer simulations. Results show observable performance enhancements compared with some benchmark strategies in terms of detection accuracy and agility. Copyright © 2015 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.     

基于压缩感知的分步合作频谱感知方法

在研究自相关矩阵检测理论的基础上,提出一种采用压缩感知的分步合作频谱感知方法.通过压缩感知将海量采样数据量减小,提取能够有效代表原信号的采样点;通过随机选择参与运算的认知用户及其数量进行合作检测,并反馈有益信息,减少了传统合作检测所有认知用户参与检测带来的运算复杂度.仿真表明该方法提高了频谱检测率,缩短了频谱检测时长,...