基于能量和协方差的两步频谱感知

频谱感知是认知无线电中的一项关键技术,主要功能是能够快速准确检测出频谱中是否存在授权用户。频谱感知的能量检测算法简单,但在低信噪比情形下的检测性能不佳,而协方差算法在低信噪比环境下具有较好检测性能。针对上述情况提出了一种这两步相结合检测的算法,从而具有更准确的频谱感知性。仿真结果表明,两步检测算法在低信噪比情况下无需授权用户的先验信息,同时使算法的平均计算量相对于协方差算法有一定程度的降低,并能有效地提高频谱感知性能。     

认知无线电中一种基于循环谱的能量检测算法

能量检测方法存在检测精度不高以及对噪声功率的不确定性敏感等问题,在认知无线电中应用时极易造成极大地虚警或漏检.为了提高认知用户接收主用户信号的检测精度,本文在详细分析循环谱理论的基础上提出了一种基于循环谱的接收信号功率检测算法,并以MPSK信号为例给出了该算法详细的理论分析.计算机模拟仿真结果表明:无论是在高信噪比还是在低信噪比条件下,基于循环谱的接收信号功率检测算法的检测精度相比传统的能量检测方法均有较大的性能增益.     

基于能量和循环平稳特征检测的CMMB主用户信号感知技术研究

认知无线电是提高频谱利用率的有效手段。CMMB是我国自主知识产权的一种移动多媒体广播制式,当CMMB主用户不在线时,次用户可以使用该频段进行通信。文章研究了基于能量的和循环平稳特征检测的CMMB主用户信号频谱感知技术。仿真结果表明:所提ED-CFD算法检测概率较ED算法有较大提高,尤其是低信噪比条件下,同时也较CFD算法大大降低了计算量。     

基于循环平稳特征的频谱感知算法概述

传统的静态频谱资源分配分配政策导致频谱利用率低下,为解决这一问题,人们提出利用认知无线电技术实现动态频谱接入.频谱感知是认知无线电的关键技术,循环平稳特征检测算法是3种常见频谱检测算法之一,但是该算法存在各种不足.首先简要介绍认知无线电的背景和概念,然后详细介绍了循环平稳特征检测算法,以及目前提出的各种基于循环平稳特征检测的增强算法,分析了各自的原理及其优缺点.     

基于循环谱能量的自适应频谱检测算法

根据信号循环平稳谱的特征,研究在低信噪比环境下的频谱检测问题,提出一种基于循环谱能量的自适应判决门限频谱检测算法。该算法融合能量检测与循环平稳特征检测的机理,以信号的循环谱能量为检测统计量,加权合并虚警率与检测率,准确估计循环谱特征值,构建了具有噪声自适应能力的频谱检测判决门限。仿真结果表明,该算法可以在低信噪比环境下有效地完成频谱检测,克服了噪声波动对频谱检测性能的影响,对不同调制主信号的感知具有稳健性。与最大—最小特征值算法和盲检测算法相比,该算法分别改善了信噪比4dB和8dB。     

基于能量和循环平稳检测的双门限两层感知算法

针对传统能量检测法容易受到噪声干扰、循环平稳检测法计算复杂度高的问题,提出了一种基于能量检测和循环平稳检测的双门限两层感知算法。利用双门限能量检测法对接收信号进行第一层检测,对于能量统计值落入双门限之间的信号,采用循环平稳检测法进行第二层检测。通过对传统能量检测法、循环平稳检测法和文中双门限两层感知算法的检测性能和复杂度进行仿真对比,结果显示在相同检测概率情况下,文中方法相较前两种方法,信噪比分别提升了2 dB和1 dB,虚警率分别降低了0.18和0.1,验证了双门限两层感知算法的有效性和可靠性。     

基于CMMB信号频谱感知和参数估计的研究

为了挖掘广播电视超高频(UHF)频谱资源的重复利用,以认知无线电研究为基础,对比了3种常用非合作式下基于发射机的频谱感知方法的优劣点。主要介绍了灵敏度较高的循环平稳特征检测算法,并完成了针对中国移动多媒体广播(CMMB)信号频谱感知的MATLAB仿真,在GUI界面实现了效果演示。     

基于D-S证据理论的循环平稳频谱协作感知

为了避免干扰授权用户的正常通信,认知无线电系统需要较好的频谱检测性能。提出了基于循环平稳特征和D-S证据理论的多天线多用户频谱协作感知方法。分析了多天线接收信号的谱相关函数,在频域按照最大比合并的方法合并各天线接收信号,得到合并信号的谱相关函数。依据谱相关函数的能量,在多用户中采用D-S证据理论做协作频谱检测。仿真分析表明,基于循环平稳特征和D-S证据理论的多天线多用户频谱协作感知方法可有效改善认知无线电系统检测性能。     

基于循环谱对称性的频谱感知算法

针对现有基于循环谱的频谱感知算法的不足,利用改进SSCA算法计算接收信号的循环谱,减少算法的计算量;利用循环谱的对称性,选择非零循环频率处的循环谱抵抗干扰和噪声,结合对称性搜索策略进行频谱感知.分析并仿真了循环谱的参数对频谱感知算法的影响,仿真结果证明了所提出算法克服了传统算法的不足,提高了低信噪比下的正确检测性能.     

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.     

Combined energy detection and one-order cyclostationary feature detection techniques in cognitive radio systems

One of the main requirements of cognitive radio systems is the ability to detect the presence of the primary user with fast speed and precise accuracy.To achieve that,a possible two-stage spectrum sensing scheme is suggested in this paper.More specifically,a fast spectrum sensing algorithm based on the energy detection is introduced focusing on the coarse detection.A complementary fine spectrum sensing algorithm adopts one-order cyclostationary properties of primary user's signals in time domain.Since the one-order feature detection is performed in time domain,the real-time operation and low-computational complexity can be achieved.Also,it drastically reduces hardware burdens and power consumption as opposed to two-order feature detection.The sensing performance of the proposed method is studied and the analytical performance results are given.The results indicate that better performance can be achieved in proposed two-stage sensing detection compared to the conventional energy detector.     

低信噪比下周期平稳信号的稳健检测算法

本文提出了一种新的对周期平稳信号进行检测以及对二阶周期循环频率进行估计的算法。该算法利用信号的递归性质构造高阶自相关矩阵,并通过利用周期平稳信号与自相关矩阵特征值和特征向量的关系,对其进行检测以及对循环频率进行估计。传统检测周期平稳信号的算法是通过计算其循环自相关函数或循环谱实现,相比传统算法而言,本算法由于利用到了信号更多的先验信息,因而在较低信噪比以及较低快拍数下对周期平稳信号均能有较好的检测性能。文中仿真实验表明,本文所提算法估计出的伪循环谱相比传统方法估计出的循环谱更为平滑,在相同快拍和信噪比条件下,检测概率均高于传统方法,特别在低信噪比下对检测概率的改善更为明显。      

认知无线电中双阶段频谱检测算法研究

在认知无线电网络中,为了实现更精确的检测,并避免对授权用户的干扰,一种双阶段频谱检测算法被提出.该算法由粗检测和细检测两种方式组成.粗检测阶段采用应用广泛的能量检测技术.由于能量检测技术的性能在衰落环境中容易受到影响,当粗检测阶段时感知结果判定为信道空闲,在细检测阶段将采用基于一阶周期平稳特征检测算法.对于这种双阶段频谱检测算法,推导分析了错误检测概率和吞吐量的性能指标.仿真结果表明,频谱检测性能显著优于常规的一阶段频谱检测算法.     

基于循环平稳分析的MPSK信号接收

提出了一种新的MPSK信号解调算法。通过对预处理后的MPSK信号进行循环平稳分析,利用已调信号的4阶循环累积量估计载波频率和初始相位偏差以便实现正交解调。由于高阶循环统计量具有抗平稳噪声的能力,因此在循环累量域有较高的参数估计精度。采用小波变换估计基带信号的码元速率,通过抽样判断产生再生基带信号从而实现了信号的盲解调。这种解调算法无需信号参数的先验信息,理论分析和实验结果证实了算法的有效性。     

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。     

Sliding window energy detection for spectrum sensing under low SNR conditions

For spectrum sensing, energy detection has the advantages of low complexity, rapid analysis, and requires no knowledge of the transmission signal, which makes it suitable for a wide range of applications. However, under low signal‐to‐noise ratio conditions, the required window length (or the time‐bandwidth product) for energy detection to achieve a desired detection performance is large. In addition, conventional energy detection assumes that the detection tests are independent, that is, there is no overlap between individual detection tests. These properties significantly reduce the detection speed when energy detection is used for the continuous monitoring over a communication channel for the detection of signal transmission activities. In this paper, we propose a sliding window detection analysis with overlap among multiple tests. Algorithms for effective performance analysis of the proposed sliding window energy detection are proposed. The impact of window length on distribution of detection time is investigated. Simulation results on the proposed sliding window energy detection are also compared with the theoretically predicted and conventional energy detection performance estimates. Copyright © 2015 John Wiley & Sons, Ltd.