认知无线电网络中物理层频谱检测算法的研究

频谱检测是认知无线电网络(CRN)的关键技术之一,本文对认知无线电网络中物理层频谱检测的算法进行了研究.首先阐述了经典检测算法的应用场景、检测性能和设备实现复杂度,针对经典算法中的问题和不足,提出一系列改进型算法以及利用信号与噪声相关性差异的新型检测算法,并对各种检测算法进行了分类比较,在此基础上提出了结合不同检测算法优势的CRN检测策略,最后指出可能的研究方向.     

卫星认知无线通信中频谱感知算法比较

以实现卫星认知无线通信中频谱空穴探测为目的,列举并比较了目前用于频谱感知的六种算法。根据各个算法的自身特点指出其应用场合,分别分析了它们的优缺点,通过计算机仿真给出了能量检测、匹配滤波和压缩感知的检测性能,并指出压缩感知对硬件复杂度的要求最小,适合卫星认知无线通信。     

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。     

先验知识未知情况下的频谱空穴检测算法

为了解决无线电频谱资源日趋匮乏的问题,对频谱空穴检测技术进行研究,设计了一种频谱空穴检测方案.首先,待检测信号通过带通滤波器,实现待检测频段的分段处理;其次,寻找到循环自相关函数的峰值,将其假定为授权信号的循环频率;最后,将该处的统计检测量与检测门限值进行比较,检测出频谱空穴,达到动态管理频谱资源,并提高频谱利用率的目的.仿真结果表明,该算法在-5 dB高斯白噪声背景下有效.     

认知无线电中基于循环统计量的频谱空穴检测方法

频谱空穴检测是认知无线电研究的关键技术.针对授权用户信号的循环平稳特性以及它和干扰信号、噪声的循环独立特性,提出了一种基于循环统计量的频谱空穴检测方案.构造了频谱空穴检测的二元假设检验模型,推导了相应的检验统计量.仿真结果表明,在低信噪比情况下,相比传统的能量检测法,该方法具有较优的检测性能,同时能有效地区分授权用户信号与同频干扰信号.     

基于优化贝叶斯压缩感知算法的频谱检测

近年来,压缩感知理论依旧是信号处理领域的研究热点之一。将压缩感知应用于频谱检测技术可以突破传统的奈奎斯特采样定理,降低检测时采样率,因此可以减轻硬件处理的压力。因此适合用在频谱检测技术中,特别是宽带信号的频谱检测。本文对贝叶斯压缩感知理论（BCS,Bayesian Compressed Sensing）进行研究,并将其引入频谱检测技术中。在BCS算法的基础上,通过进一步减小高斯随机观测矩阵列向量的相关度,实现对观测矩阵的优化,得到一种优化的贝叶斯压缩感知算法（称其为OBCS算法,即Optimized BCS）。在MATLAB仿真中,本文提出将数零法作为频谱检测判决规则,并使用BCS和OMP算法作为对照,验证了OBCS算法无论在重构误差、检测概率还是虚警概率等指标上都具有最佳的效果。      

采用压缩采样匹配追踪算法的频谱感知

频谱资源的匮乏成为无线电发展的瓶颈,解决频率匮乏有两类方法:一是提高频谱利用率;二是扩大可利用的频率范围。频谱感知技术能提高频谱利用率,但在高频的应用中会面对过高的采样速率、较大的数据量,这对硬件实现提出了艰巨的挑战。本文根据无线电频谱稀疏性介绍一种基于调制宽带转换器的压缩采样匹配追踪（CoSaMP）算法。本文利用调制宽带转换器对无线电信号进行亚奈奎斯特采样,再利用CoSaMP算法对采样后的自相关矩阵求解。本文的方法不仅能应用在更高的频谱,且能提高频谱利用率。仿真结果表明:该方法能在能以一个较低的采样速率对信号进行采样,且CoSaMP算法的恢复误差要小于OMP和ROMP算法。      

基于压缩感知信道能量观测的协作频谱感知算法

压缩感知为认知无线电宽带频谱感知提供了一种新思路。基于压缩感知原理,该文提出一种不需要重构宽带频谱本身,而是直接重构各信道能量的协作频谱感知方法。多个次用户使用宽带随机滤波器组获取信道能量的观测值。融合中心同步接收多个用户的能量观测,并利用同步稀疏自适应匹配追踪协作重构算法重构所有次用户的信道能量。仿真结果表明加性高斯白噪声环境下该协作感知方法所需的滤波器数目仅为传统方法的20%左右,瑞利衰落信道下也仅需传统方法的40%,有效降低了系统复杂度并改善感知性能。同时,该文提出的同步稀疏自适应匹配追踪算法对比经典的同步正交匹配追踪算法在重构精度及算法复杂度两方面都有所提升。     

认知无线电中基于机器学习的频谱感知算法研究

针对于认知无线电中传统感知算法受信噪比(SNR)影响、过度依赖主用户先验知识和感知时间长等问题,提出基于支持向量机(SVM)的频谱感知算法,通过将信号能量值、SNR值与类别标签作为训练数据,对其进行SVM学习后,得出此CR环境下的分类模型。仿真结果显示在低SNR环境下,机器学习频谱感知算法检测概率比能量检测的提高了近40%,分类错误率仅为1.4%,因此具有更优良的感知性能。     

频谱空穴检测及其仿真

感知无线电接收机为了感知其周围的无线电环境,首要的工作就是对其周围存在的信号进行检测。本文针对感知无线电系统中最为关键的频谱空穴检测技术进行了研究。通过对3种信号检测技术的比较,选择循环平稳特征检测法作为感知无线频谱的方法并对该方法进行了仿真。此外．对控制实体根据频谱感知的结果、从频谱中检测出频谱空穴区域的功能、以及感知无线电接收机与感知无线电发射机进行协调的功能也进行了仿真。     

A directly seeking spectrum holes algorithm by compressive sampling

The method of cognitive radio (CR) is a promising solution to the problem of spectrum scarcity. One of the crucial tasks in the CR is the spectrum hole (SH) detection. The energy detection (ED) method is the most dominant spectrum sensing approach owing to its low computational complexity and the ability to identify SHs without requiring a priori knowledge of primary transmission characteristics. But it will be accompanied by some problems such as the high sampling rates, the difficult setting for detection threshold, and the complexity. An improved algorithm with directly seeking SHs from compressive sampling via compressive sensing algorithm is proposed in this paper. The sampling rate is decreased by the process of the compressive sampling, and the computation complexity is reduced for the elimination of the construction stage in the proposed algorithm. Besides, the detection threshold is not needed to be set for the method of relative comparison. The simulation results show that the proposed algorithm has a similar probability of detection (POD) of SHs to the traditional ED algorithm and the compressive spectrum sensing algorithm with minimum sampling numbers and lower computation complexity on the condition that the signal noise ratio is beyond 0 dB. It means the proposed algorithm obtains the balance between computing complexity and the sampling rate, and the performance of SH detection is maintained at the same time.     

Joint cooperative spectrum sensing and channel selection optimization for satellite communication systems based on cognitive radio

Cognitive radio has attracted considerable attention because of its ability to make full use of the available spectrum resources for wireless terrestrial communication networks. In addition, the satellite communication scenario, which requires a transparent air interface to integrated/hybrid Satellite–Terrestrial communication systems and provides a supplement for other multimedia services, will cause frequency scarcity. Satellite communication systems based on cognitive radio are available under scenarios that involve transmission with changing communications. In this paper, a cooperative spectrum‐sensing algorithm based on a time or bandwidth‐based cooperative spectrum‐sensing model of an integrated/hybrid cooperative satellite communication system is proposed. Moreover, the concept of weighted cooperative spectrum sensing is introduced. Compared with the traditional single‐user spectrum‐sensing algorithm, the cooperative spectrum sensing is able to cope with the interference to the primary user caused by a secondary user better. In addition, multiple earth stations that use some part of the bandwidth cooperatively to perform spectrum sensing throughout the whole frame can detect the presence of primary user in time. The satellite component combines the sensing results from earth stations to reach a final decision, and the optimal combination weights to maximize the detection probability of the secondary user are obtained. Numerical results that demonstrate the performance of the proposed algorithm are presented. Copyright © 2015 John Wiley & Sons, Ltd.     

Modified Bayesian algorithm‐based compressive sampling for wideband spectrum sensing in cognitive radio network using wavelet transform

This paper presents the implementation of a modified version of Bayesian relevance vector machine (RVM)‐based compressive sensing method on cognitive radio network with wavelet transform for spectrum hole detection. Bayesian compressive sensing is used in this work to deal with the complexity and uncertainty of the process. The dependency of the Bayesian compressive sensing on the knowledge of noise levels in the measurement has been relaxed through the proposed Bayesian RVM‐based compressive sensing algorithm. This technique recovers the wideband signals even with fewer measurements maintaining considerably good accuracy and speed. Wavelet transform is used in this paper to enable the detection of primary user (PU) even in the low regulated transmission from unlicensed user. The advantage of this approach lies in the fact that it enables the evaluation of all possible hypotheses simultaneously in the global optimization framework. Simulation study is performed to evaluate the efficacy of the proposed technique over the cognitive radio environment. The performance of the proposed technique is compared with the conventional Bayesian approach on the basis of recovery error, recovery time and covariance to verify its superiority.     

一种基于TOPSIS信道排序的新频谱切换方案

将接近理想方案的序数偏好法(TOPSIS)应用于认知无线电网络的频谱切换中,通过对 影响切换性能的4个参数的融合,设计了一种基于TOPSIS算法的信道排序方案,通过仿真验 证,设计了各参数的权值。统计结果表明,提出的算法在80%的情况下要优于传统的切换算 法,可以有效减少认知用户的切换次数,提高有效数据传输速率,降低认知用户的通信中断 概率。     

基于特征扩频的卫星转发器频谱资源聚合研究

针对CDMA卫星通信系统受到严重外部干扰,且可连续使用的频谱受限问题,提出3种基于特征扩频的卫星转发器频谱聚合方案,实现多个转发器频谱高效聚合的同时对抗系统受到的外部干扰。通过仿真表明,所提方案能够克服基于现有认知多载波CDMA方法进行卫星转发器频谱聚合的设计复杂度较高、频谱聚合效率低的缺点,并且所提整体特征扩频方案在性能和支持用户数方面均优于另外2种多载波特征扩频方案,提高了系统对多个转发器的非连续频谱利用率,进而提升系统容量。     

A novel spectrum sharing scheme for cognitive radios

A novel approach, which combines spectrum adaptation and orthogonal frequency division multiplexing (OFDM), is proposed to share the licensed spectrum dynamically for cognitive radio systems. Given spectrum sensing and channel estimation information by the receiver, an improved model due to signal power thresholds is adopted to achieve spectrum adaptation for unlicensed users. In order to efficiently allocate the unlicensed signal power, a dynamic power allocation algorithm is also proposed. Simulation results indicate that the propositional scheme solves the partial interference problem of interference temperature model (ITM) and improves the spectrum utilization.     

认知卫星通信频谱感知及资源分配技术综述

由于卫星频谱资源日益短缺,逐渐出现了资源"假性枯竭"的问题,但通信系统的频谱利用率却很低,因此必须提高卫星网络的频谱利用率.认知卫星通信能够解决这一问题.为了能够更好地研究认知卫星通信,简要阐述了认知无线电的基本原理,介绍了认知卫星通信的应用场景,通过分析和对比,总结了频谱感知及分配技术和功率控制技术的研究现状和优缺点...     

协作频谱感知中的动态信任评估机制

针对动态性SSDF攻击对协作频谱感知技术的危害性,实时观察分析认知用户的感知行为,提出一种动态信任评估机制.根据认知用户的历史感知变化情况,引入时间衰减因子、加性奖励因子和加性惩罚因子,计算出随时间和协作次数不断变化的动态信任值,选取可信认知用户参与协作感知,提高了数据融合中心的协作判决准确性.仿真结果表明,动态信任机制可以有效抑制恶意用户的信任值增长,降低对“OR”、“AND”和“Majority”3种常用协作频谱感知数据融合准则的攻击成功率.     

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.