基于卷积神经网络的无线电广播同频干扰检测

针对无线电干扰中较为突出的同频干扰问题,将深度学习应用于干扰信号检测,提出一种无线电调频广播同频干扰检测算法。将调频广播数据转化为能体现信号特性的小波变换时频图,并将其作为卷积神经网络(CNN)的训练数据,训练CNN学习信号的时频特征,得到干扰检测模型。实验结果表明,与传统的机器学习算法相比,该算法能更准确地检测出广播信号中是否存在同频干扰信号,其干扰检测准确率达95.0%。     

基于循环平稳的图样特征识别频谱检测方法

频谱空穴检测是认知无线电研究的关键技术。针对认知无线电系统中甚低信噪比环境下频谱检测的困难,基于循环平稳理论,提出对接收信号的循环谱密度函数俯视图特殊图样的模式识别来进行频谱检测判决的方法。由此设计出谱峰搜索检测与图样特征识别相结合的频谱检测判决机制。实验仿真结果表明,所提出的检测方法性能良好,可以有效地对弱主用户信号进行频谱检测。     

无线防盗报警设备中同频干扰信号软件检测方法

描述了无线探测器同频干扰现象对无线报警器系统带来的危害,在简要介绍编码芯片信息帧格式、接收电路内部噪声与外部杂散电磁波干扰输出特性基础上,详细分析了各类同频干扰信号的来源及其特征,提出了一种简单、有效的同频干扰信号检测方法,给出了完整的检测流程与检测参数的选择依据,指出了系统受到恶意同频干扰后的动作.该方法可在基于MCU软件解码过程中同步进行,MCU资源占用率低、响应速度快且可靠性高,能准确识别周围无线探测器正常操作触发信号与恶意同频干扰信号,有效地提高了无线防盗报警系统的可靠性.     

一种无线传感器网络调制方式的仿真和研究

当前,存在着蓝牙、无线局域网等无线标准,它们的功耗相对比较高,成本高,不适用于低能耗的应用,如无线传感器网络.新的无线传感器网络调制方法--基于超宽带信号的多频带OFDM调制方法,可以有效的降低无线传感器网络的能耗.通过Matlab工具仿真了多频带OFDM调制信号和功率谱密度.比较当前无线标准,分析了频段间不干扰性和多频带OFDM调制功率,并提出了自适应子频带选择算法.通过仿真和分析,可以得出OFDM调制功耗低,能提供良好鲁棒干扰与共存性,能适应多种不同的环境.基于超宽带信号的多频带OFDM调制是一种集成到WSM中的,并能代替传统的无线电收发机的比较划算方法,具有一定的应用前景.     

基于NS2的高密度WLAN同频干扰

首先简单介绍了无线局域网同频干扰产生的原因,然后在NS2仿真平台上搭建高密度无线局域网环境.通过仿真,测量系统中总的数据吞吐量、端到端传输时延和平均吞吐量来探究高密度WLAN下同频干扰强弱程度随AP数增加的变化趋势.仿真结果表明,高密度WLAN下同频干扰强弱程度随AP数的增加遵循一定的变化规律,这为实际规划接入节点时同频干扰强弱的控制提供了依据,也为仿真研究高密度无线局域网提供了参考.     

CR系统中基于NPGP的功率控制算法

为解决认知无线电（cR）系统中认知用户对主用户的干扰及系统功率控制问题,在介绍认知无线电原理及其基本在线认知任务循环框图的基础上,将DavidGoodman等人提出的基于非合作带竞价博弈的功率控制算法应用到认知无线电系统中。与传统的功率控制算法相比,该算法不仅降低了认知无线电系统中认知用户的发射功率,而且降低了认知用户之间的干扰,提高了系统的整体性能。最后通过MATLAB仿真分析比较了带价格因子和不带价格因子两种情况下的性能。     

一种新的跳频信号检测算法

本文提出了一种基于功率谱估计的跳频信号检测的新方法,该方法主要是利用定频信号、跳频信号的功率谱随时间变化的差异性,通过对定频信号功率谱进行对消以实现跳频信号的检测,分析了影响定频信号功率谱对消的因素,计算机仿真结果证实了该方法的有效性。     

认知无线电技术在 ZigBee 中的应用研究

目前多种无线通信技术共享2.4GHz ISM 频段,它们之间的相互干扰以及频谱重叠现象已成为人们非常关注的一个问题.文中将认知无线电技术应用到 ZigBee 网络通信中,针对2.4GHz 频段,利用认知无线电的频谱感知功能,对信道状态进行检测,搜寻频谱空穴,并且对频谱进行长期感知和统计,使 ZigBee 用户选择最可能空闲的频段作为传输信道,同时提出了一个2.4GHz 无线环境感知模型.该方法提高了 ISM 频段的频谱利用率,并且减少了同频段其他多种无线通信技术对 ZigBee 产生的干扰,保证了 ZigBee 信号的有效传输     

短波信道下跳频信号检测

跳频信号检测是当前通信对抗领域紧迫而困难的任务之一,提出了一种在复杂短波环境下有效检测跳频信号的新方法。首先,对已有动态门限算法进行改进,提出一种新的估计噪声基底的方法;用该方法对信号时频图每个时间单元的功率谱图进行滤波,将信号的时频图降噪处理;然后根据短波信道特点设计了参数统计规则,得到信号描述表,最后采用直方图方法对各信号持续时间统计分类判断出是否存在跳频信号。仿真实验证明,该方法运算简单,能够较好地解决噪声和干扰较大的复杂短波信道环境下跳频信号的检测问题。     

认知无线电技术在ZigBee中的应用研究

目前多种无线通信技术共享2．4GHzISM频段,它们之间的相互干扰以及频谱重叠现象已成为人们非常关注的一个问题。文中将认知无线电技术应用到ZigBee网络通信中,针对2．4GHz频段,利用认知无线电的频谱感知功能,对信道状态进行检测,搜寻频谱空穴,并且对频谱进行长期感知和统计,使ZigBee用户选择最可能空闲的频段作为传输信道,同时提出了一个2．4GHz无线环境感知模型。该方法提高了ISM频段的频谱利用率,并且减少了同频段其他多种无线通信技术对ZigBee产生的干扰,保证了ZigBee信号的有效传输。     

The performance evaluation of a spectrum sensing implementation using an automatic modulation classification detection method with a Universal Software Radio Peripheral

Based on the inherent capability of automatic modulation classification (AMC), a new spectrum sensing method is proposed in this paper that can detect all forms of primary users’ signals in a cognitive radio environment. The study presented in this paper focuses on the sensing of some combined analog and digitally primary modulated signals. In achieving this objective, a combined analog and digital automatic modulation classifier was developed using an artificial neural network (ANN). The ANN classifier was combined with a GNU Radio and Universal Software Radio Peripheral version 2 (USRP2) to develop the Cognitive Radio Engine (CRE) for detecting primary users’ signals in a cognitive radio environment. The detailed information on the development and performance of the CRE are presented in this paper. The performance evaluation of the developed CRE shows that the engine can reliably detect all the primary modulated signals considered. Comparative performance evaluation carried out on the detection method presented in this paper shows that the proposed detection method performs favorably against the energy detection method currently acclaimed the best detection method. The study results reveal that a single detection method that can reliably detect all forms of primary radio signals in a cognitive radio environment, can only be developed if a feature common to all radio signals is used in its development rather than using features that are peculiar to certain signal types only.     

认知无线电网络中宽频谱的信号分离算法

在认知无线电网络中,认知用户随机接入宽带频谱进行数据传输,但是这样很容易受到恶意用户的干扰,这些恶意用户随意地接入共享频带进行信号传输,这些信号会干扰主用户和认知用户。为此,提出了一种基于压缩感知的信号分离方法。该方法可以很好地从宽带信号中分离出恶意用户信号。算法主要采用以下三个步骤：（1）所有认知用户采用压缩感知技术从宽带频谱中恢复各信号;（2）认知用户将分离的信号发送到融合中心,融合中心通过小波边缘检测的方法确定频谱边缘,并按照边缘特性将频谱分成若干频段;（3）融合中心根据具体特征对每个子频段进行信号分离。分析和仿真结果表明,这种新的基于压缩感知的宽频带信号分离方法能很好地从宽带信号中将含有恶意用户干扰的混合信号分离出来。     

RAC: Range Adaptive Cognitive Radio Networks

In recent years, cognitive radio has received a great attention due to tremendous potential to improve the utilization of the radio spectrum by efficiently reusing and sharing the licensed spectrum bands, as long as the interference power inflicted on the primary users of the band remains below a predefined threshold level. Cognitive radio allows the secondary users in the cognitive radio network to access the licensed spectrum of the primary users opportunistically. In this paper, an autonomous distributed adaptive transmission range control scheme for cognitive radio networks which is called the RAC is proposed. The RAC considers the QoS requirements of both the primary and the secondary users simultaneously. The cognitive user's maximization of its achievable throughput without interfering the primary user by adapting transmission range of the secondary users dynamically is the key feature of the RAC. One of the advantages of using the proposed scheme is its implementation simplicity. The RAC is compared to other cognitive radio schemes in a simulation environment by using ns2. Simulations indicate that, the RAC can well fit into the mobile cognitive radio ad hoc networks and improve the network performance. Having compared to the other schemes utilizing contemporary cognitive radio technology, the RAC provides better adaptability to the environment and maximizes throughput and minimizes data delivery latency.     

基于PCA与主动学习AdaBoost的频谱感知算法

针对认知网络中各低信噪比环境下主用户信号检测率偏低的问题,提出一种基于主成分分析和主动学习AdaBoost的主用户信号频谱感知算法.该算法首先采用主成分分析算法对信号特征参数进行提取,获得信号的主成分,之后利用主动学习算法通过多次迭代抽样,获取有利于提高分类性能的样本,并对AdaBoost分类器进行训练,最后利用训练完成的AdaBoost分类器对待测信号进行分类检测.仿真实验表明,在各低信噪比情况下与ANN和MME算法相比较,所提算法具有较高的分类感知性能,有效地实现了对主用户信号的频谱感知.     

异构无线网络的认知节点位置分析

针对异构无线网络的协同频谱感知的检测能力问题,提出了一种基于信号相关特性的协同判决策略,采用环状对称的认知节点预布置方法来提高预定区域内主用户的检测能力.通过对称布置认知节点对之间的协同检测来减少隐藏终端误判概率,解决双工状态的主用户检测问题并实现对处于接收状态的异构网络主用户的非协议解析.数值仿真验证了该认知节点预布...     

On detecting primary user emulation attack using channel impulse response in the cognitive radio network

Cognitive radio is an effective technology to alleviate the spectrum resource scarcity problem by opportunistically allocating the spare spectrum to unauthorized users. However, a serious denial-of-service (DoS) attack, named the ‘primary user emulation attack (PUEA)’, exists in the network to deteriorate the system performance. In this paper, we propose a PUEA detection method that exploits the radio channel information to detect the PUEA in the cognitive radio network. In the proposed method, the uniqueness of the channel impulse response (CIR) between the secondary user (SU) and the signal source is used to determine whether the received signal is transmitted by the primary user (PU) or the primary user emulator (PUE). The closed-form expressions for the false-alarm probability and the detection probability of the proposed PUEA detection method are derived. In addition, a modified subspace-based blind channel estimation method is presented to estimate the CIR, in order for the proposed PUEA detection method to work in the scenario where the SU has no prior knowledge about the structure and content of the PU signal. Numerical results show that the proposed PUEA detection method performs well although the difference in channel characteristics between the PU and PUE is small.     

认知无线电网络中基于和声搜索的频谱分配与功率控制

针对认知无线电网络中功率控制和频谱分配过程存在互相影响的问题,提出一种基于和声搜索的频谱分配和功率控制算法。通过综合分析频谱分配和功率控制过程中的各种约束条件,建立了联合功率控制和频谱分配的系统模型。算法根据系统模型特点设计和声搜索算法下相应编码方案,采用多目标优化方法处理复杂的约束条件,并赋予可行解适当的优先权重。仿真实验表明,算法可以很好地解决认知无线电网络中的频谱分配和功率控制问题。     

信息论准则的频谱感知技术

频谱感知是认知无线电通信的前提,针对传统单天线能量检测算法易受噪声不确定性影响的问题,结合MIMO的空间处理能力,提出一种基于信息论准则的频谱感知算法。首先通过实时侦听信道,获得观测信号的相关矩阵;然后利用AIC准则检测周围环境中是否有主用户存在。该算法无需预先得知噪声的功率信息、无需设置判决门限。仿真结果表明,相比于能量检测算法,该算法有效提高了系统的检测概率,对噪声不确定性具有鲁棒性。     

基于无线环境图信息辅助的多循环频率协作频谱感知方法

针对频谱感知中单循环频率检测不能充分利用信号循环谱信息的缺点,本文提出一种基于无线环境图(radio environment map,REM)信息辅助的多循环频率协作频谱感知方法.本文方法第1步在多个认知用户处分别选取多个相同的循环频率进行循环平稳检测,选取谱相关函数幅度作为检测统计量,根据推导的判决门限公式设定恒虚警...