基于双门限能量检测的自适应协作频谱感知

针对认知无线电中传统单门限能量检测由于单一门限造成的低信噪比情况下容易误判从而导致错失频谱接入机会的不足,提出了一种基于双门限能量检测方法的自适应协作频谱感知模型.该模型以加性高斯白噪声信道模型为基础,由传统双门限能量检测方法改进而成,针对接收到的能量统计值的大小采用不同的判决方法,各个判决结果直接由所采用的判决方法决定.仿真结果表明,在较低信噪比条件下,与传统单门限能量检测模型相比,该自适应协作频谱感知模型具有更好的识别性能,随着用户数量的增加,识别性能更优.     

认知无线网络中动态双门限协作频谱感知性能的优化方案

频谱感知作为认知无线电的关键技术,得到广泛深入的研究。其中衡量协作频谱感知性能的主要参数为全局虚警概率和全局漏检概率,它们之和被定义为全局错误概率。本文研究基于双门限能量检测的协作频谱感知性能的优化方案,首先,固定双门限能量检测的检测门限值,对表决融合准则的投票门限进行优化,使得在该能量检测门限值条件下,协作频谱感知的全局错误概率最小;然后在表决融合准则的投票门限取最优值的前提下,对双门限能量检测的检测门限值进行了优化,在不同接收信噪比条件下,最优的检测门限值是动态的,所以要根据信噪比确定最优的检测门限值,使得协作频谱感知的全局错误概率在各信噪比条件下都达到最小值,从而提高了协作频谱感知的性能。仿真结果表明,表决融合准则的投票门限和双门限能量检测的检测门限值取得各自的最优值时,全局错误概率最低,检测性能最好。      

基于随机共振的双门限协作频谱感知算法

针对现有频谱感知算法在低信噪比（SNR）环境中性能检测不佳的问题以及传统随机共振（SR）检测弱信号的方法在实际应用中存在的局限性,通过设置最优门限,计算出最优的协作用户数量,提出了一种基于随机共振的双门限协作频谱感知算法,并对提出的算法进行了性能分析。DCSSR算法通过将位于双门限不确定区域的统计数据经过随机共振系统,进一步提高频谱感知算法在低信噪比下的检测性能。仿真结果表明,在不同信噪比和虚警概率下,DCSSR算法相较于传统单门限能量协作算法、双门限能量协作算法以及单门限随机共振协作算法,检测性能都得到了提升。在信噪比为-20 dB时,提出的DCSSR算法相较于传统单门限能量检测协作算法,检测概率提高了80%。     

认知无线电中协作压缩频谱感知算法

针对宽带频谱认知无线电环境中,传统能量检测法在信噪比较低时,容易出现误检而使系统的检测性能下降的问题,文中提出了一种新型高性能的协作频谱感知算法,它是基于压缩理论的多节点频谱感知方法,各节点之间采用基于双判决门限的协作方式。仿真结果显示,双门限协作压缩频谱感知算法在低信噪比的情况下,检测性能明显优于传统能量检测法。     

改进双门限能量检测分簇协作频谱感知算法

针对传统频谱感知算法在低信噪比环境下检测概率较低的问题,提出改进双门限能量检测分簇协作频谱感知算法。算法将感知节点分簇,簇间信息采用OR准则硬融合,簇内双门限外节点发送1 bit判决结果进行硬融合,双门限内节点发送能量值和信噪比值进行加权软融合。加权软融合阶段构造检测概率与节点权重系数函数,利用压缩因子粒子群算法选择权重系数进行函数寻优,以最大化检测概率。仿真结果表明,在低信噪比和不同感知用户数目环境下,算法仍具有较高的检测概率。     

一种双门限分簇协作频谱智能感知算法

基于门限值的能量检测是一种常用频谱感知技术,传统单门限能量检测方法不灵活且不准确.本文提出了一种基于双门限分簇自适应协作频谱感知算法.首先,基于噪声不确定性设置双门限值,在双门限值范围外进行硬判决,否则进行软判决.根据判决结果,基站将传感器节点划分为不同的簇.融合中心根据融合规则,设置分簇门限值,进行进一步频谱检测.仿...     

基于马尔科夫模型的认知无线电动态双门限能量检测策略

该文针对低信噪比条件下频谱感知精度低的问题,提出一种基于马尔科夫模型的动态双门限能量检测算法。该算法根据信道时变特性建立基于马尔科夫的频谱占用模型,利用信道历史状态信息实现模型参数的修正。然后采用先听后说的机制对处于双门限之间的困惑信道状态进行判决,并详细分析了噪声不确定性对频谱感知性能的影响。在此基础上,为了克服噪声不确定性的影响,以频谱检测概率最大为优化目标,对双门限进行实时更新。仿真结果表明,所提频谱感知算法在减小噪声不确定性影响的同时增加了频谱感知精度,降低了认知用户的感知时间。     

基于动态门限的频谱感知算法研究

认知无线电能量检测算法在实际工程应用中非常广泛,但是该算法的主要缺点是判决门限难,很难在同时兼顾虚警概率和漏警概率的情况下对门限进行设置。因此,在能量检测算法的基础上,针对噪声平均功率存在波动性这一现状,提出了一种基于动态门限的频谱感知算法。仿真结果表明,该算法能够同时兼顾虚警概率和漏警概率,始终保证整体的频谱检测差错概率最小,具有可行性。     

一种优化的认知无线电频谱感知策略

协作频谱感知技术可以有效地避免频谱感知过程中的隐终端问题,降低感知用户对主用户的干扰。但是随着协作感知中感知用户数目的增加,感知中的通信量也会增加。相对于传统的协作感知单门限判决法,双门限判决法可以在对感知性能影响很小的情况下,降低协作感知过程中的通信量。在传统的双门限感知技术的基础上,提出了一种基于权重的双门限协作算法。仿真结果表明,在保证较小的感知通信量下,相对于传统的双门限判决,提出的算法可以提高系统的感知性能。     

Femtocell网络中基于双门限的两层协作频谱感知技术

在Femtocell和Macrocell构成的两层异构网络中,前人提出运用认知无线电的技术来解决网络中存在的干扰问题,但大多数研究主要集中在频谱资源的管理上,没有提出高效的频谱检测方法。本文结合认知无线电中频谱感知技术提出了基于双门限的两层协作频谱感知,检测出空洞的频谱资源分配给Femtocell用户使用,既能提高频谱资源的利用率,又能有效的抑制Femtocell与Macrocell之间的干扰。文中推导出了Femtocell用户基于双门限的两层频谱感知的检测概率和虚警概率,给出了Femtocell网络中感知信息两比特编码的融合准则和基于双门限的两层协作频谱感知的具体实施方法。仿真结果表明,所提算法能够有效提高Femtocell用户的频谱检测概率,通过对感知信息进行两比特编码,再将编码后的信息发送至融合中心进行融合,能够有效的提高整个系统的检测性能,抗噪声能力强。      

Cooperative Spectrum Sensing with Adaptive Double-Threshold Based Energy Detector in Cognitive Radio Networks

Spectrum sensing is one of the key functionalities in the implementation of cognitive radio. It is used to sense the unused spectrum in an opportunistic manner. In this paper, we propose an energy detector with adaptive double-threshold for spectrum sensing, to optimize the detection performance at a fixed probability of false alarm $(\text{ P }_\mathrm{f})$ i.e. 0.1, which also overcomes sensing failure problem. In the present work, the detection threshold is made adaptive to the fluctuation of the received signal power in each local detector of cognitive radio (CR) user. Simulation results show that proposed scheme optimizes better detection performance and outperforms both conventional energy detector and cooperative spectrum sensing (CSS) method by 12.8 and 3.3 % at $-$ 8 dB signal to noise ratio (SNR), respectively. While utilizing CSS with proposed adaptive double-threshold scheme, where each CR user use a double threshold detectors for local detection and send detection decisions to fusion center (FC) to give the final decision based on hard decision rule. It is further found that CSS with adaptive double-threshold improves detection performance around 26.8 and 7.6 % as compare to CSS with single threshold and Hierarchical with quantization method at $-$ 10 dB SNR, respectively, under the case when a small number of sensing nodes are used in spectrum sensing.     

Double‐threshold cooperative detection for cognitive radio based on weighing

In cognitive radio (CR), the single‐threshold cooperative detection is sensitive to the noise power. In this paper, a double‐threshold cooperative detection scheme based on weighed combination is proposed to improve the global detected performance of the cooperative detection. The double thresholds that are decided by the restriction probability are adopted to divide the energy statistics observed by CRs into three subareas, and the detected performance of the CRs locating in the confusion area is fortified through the weighed data fusion by the coordinator. The CRs in the other two areas can make local binary decisions because of their exact sensing performance and then forward their 1‐bit decisions to the coordinator that will combine all the received decisions to give the final decision on the presence of the primary user. In this paper, both the periodic single‐band and wideband cooperative detections are investigated, and the probabilities of spectrum utilization by these two patterns are respectively analyzed. The simulation shows that the detection probability of the proposed scheme is better than that of the single‐threshold cooperative detection with decision fusion but slightly worse than that of the single‐threshold cooperative detection with data fusion. However, the average number of the bits sent to the coordinator by the proposed algorithm is less than that by the data fusion, and it may increase by the decreasing of the restriction probability. The simulation also shows that the periodic wideband sensing can obtain higher spectrum utilization than the periodic single‐band sensing. Copyright © 2012 John Wiley & Sons, Ltd.     

一种基于能量检测的协作式频谱感知算法

为提高认知无线电系统中频谱检测的可靠性,提出了一种基于能量检测的协作式频谱感知算法。利用授权用户的状态在相邻感知帧之间变化的概率小这一特性,通过将当前感知帧的能量值与相邻值相结合来判断授权用户状态,这样当授权用户使用授权频段时,所提算法能有效减小采样信号能量值骤减时发生误判的概率。另外给出了所提算法检测概率和虚警概率的闭式表达式。理论分析和仿真结果表明,所提算法比传统的协作式频谱检测算法检测性能好。     

Scheme of Cooperative Spectrum Sensing Based on Adaptive Decision Fusion Algorithm

Spectrum sensing is one of the core technologies for cognitive radios(CR),where reliable detection of the signals of primary users(PUs) is precondition for implementing the CR systems.A cooperative spectrum sensing scheme based on an adaptive decision fusion algorithm for spectrum sensing in CR is proposed in this paper.This scheme can estimate the PU prior probability and the miss detection and false alarm probabilities of various secondary users(SU),and make the local decision with the Chair-Varshney rule so that the decisions fusion can be done for the global decision.Simulation results show that the false alarm and miss detection probabilities resulted from the proposed algorithm are significantly lower than those of the single SU,and the performance of the scheme outperforms that of the cooperative detection by using the conventional decision fusion algorithms.     

Optimal multi-threshold quantization scheme for bioinformatics inspired cooperative spectrum sensing in cognitive radio networks

Hard decision combination provides bandwidth efficiency but the results produced are unreliable while soft decision combination has better results but at the expense of much consumption of bandwidth. An acceptable trade-off is achieved between the two in case of quantized decision combination. In this paper an optimal quantization scheme is proposed in which the local sensing information is quantized so the maximum detection probability is met while the false alarm probability remains under a certain constraint. The proposed optimal scheme works on the basis of energy detection and the local quantization thresholds are found through iterative search. Smith–Waterman algorithm (SWA) is used to compare the local sensing reports of the CR users and similarity indexes are found for the CR users. The local sensing decisions of the CR users below a certain calculated threshold are rejected and are not included in the final decision combination at the FC. For detailed analysis, SWA-based rules of decision combination with optimal quantization thresholds are compared with a scheme that employs SWA-based rules of decision combination with heuristically selected quantization thresholds and a conventional majority combination scheme. Simulation results show that the proposed scheme performs better than the other two schemes.     

基于自适应决策融合的合作频谱感知方法

频谱感知是认知无线电(CR)的关键技术之一。在该机制中,对主用户(PU)信号的可靠检测是实现CR的前提。提出一种基于自适应决策融合的合作频谱感知算法用于频谱感知,该算法通过估计PU的先验概率与各个CR用户(SU)的漏检及虚警概率,然后运用Chair-Varshney准则对局部判决进行决策融合以得到全局判决。仿真结果表明,采用该方案的全局虚警和漏检概率明显低于单个SU,可有效提高CR系统频谱感知的可靠性。