基于可靠次用户信息的协作频谱感知算法研究

对认知无线电系统最基本要求之一就是次用户必须有能力以高的精确率来确定主用户是否存在。而以前对认知无线电频谱感知的研究表明:在实际认知网络中次用户之间的相互协作可以提高其频谱检测性能。然而,对于协作频谱感知而言,随着协作次用户数目的增加,势必会增大用于传输本地检测结果到融合中心的专用控制信道带宽,从而增加系统开销。该文在控制信道带宽有限的约束条件下,提出一种通过考虑可靠次用户信息的协作频谱感知算法来进一步改善频谱检测的性能。该算法的基本思想:只有具有可靠的本地检测结果的次用户才发送自己的检测结果到融合中心,否则,该次用户不发送任何信息。同时,对提出的该算法在理论上进行了推导,通过仿真结果表明:在控制信道带宽受限的约束下,相比于传统的或门协作频谱感知算法,提出的算法能够大大改善对主用户的检测性能。     

衰落信道下基于簇的协作频谱感知分析

在分布式协作频谱感知网络中,认知用户向融合中心上报本地检测的信道是带宽受限的,并且受各种衰落的影响。分析了衰落信道下认知用户通过"与"规则进行融合的协作感知策略,提出了认知用户间为Nakagami信道时基于簇理论的协作感知方案,推导得出了2种方法的检测概率和归一化平均感知比特数。仿真结果表明,基于簇理论的协作感知通过牺牲一定的信令开销得到较好的感知性能。     

采用最小最大准则的协作频谱感知融合

给出了采用最小最大准则实现认知无线电系统协作频谱感知融合的方法,以在主用户出现在授权频段的先验概率未知的情况下利用概率计算实现认知无线电系统的协作频谱感知融合。该方法可实现同步和异步感知信息的融合。仿真验证了算法的性能,并与采用估计主用户出现在授权频段的先验概率并进行基于概率的感知融合算法性能进行了比较。结果表明:给出的算法可有效实现主用户出现在授权频段的先验概率未知时的协作频谱感知融合。     

协作频谱感知中数据融合与决策算法比较

协作频谱感知中融合多个认知用户的本地检测结果并准确判决至关重要.研究了基于大数合并的硬判决和基于置信(最大似然)合并的软判决,对不同算法的检测性能和复杂度进行了定性和定量的分析和比较.指出未来协作频谱感知中应结合协作用户数的优化和控制信道条件进行数据融合和决策算法设计.     

集中式双非参量累积和的合作频谱感知技术

针对认知无线电网络频谱感知的检测时延降低问题，提出了一种采用双非参量累积和的合作频谱感知方法。在单主用户认知网络中，本地认知用户执行非参量累积和算法，处理能量观测数据，以缩短检测时延，减少对主用户先验信息的需求，同时为了降低带宽开销，只向融合中心传输1比特的预判决结果。融合中心在噪声干扰下接收融合预判决结果，执行非参量累积和算法，累加判决统计量，对主用户信号是否存在进行最终判决。仿真结果表明，在10%的虚警概率下，相比于传统的非参量合作频谱感知算法，双非参量累积和算法具有较低的检测延迟。      

协作认知网络中基于融合准则与感知时间联合优化的策略

在协作频谱感知网络中,感知时间和数据融合准则均影响着感知性能.假设控制信道为二进制对称信道的前提下,基于“k秩准则”建立了协作感知网络吞吐量优化问题的数学模型,目的是在保护主用户利益的前提下联合优化感知时间和k值使认知网络吞吐量最大化.理论分析了最优感知时间和k值的存在性,并进行了相关的计算机仿真.仿真结果表明:所提议...     

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。      

一种基于数据融合的合作频谱感知技术

认知无线电是为了提高频谱利用率而提出的一种智能频谱共享技术,快速可靠的检测到主用户和频谱空穴是认知无线电实现的关键和前提.由于阴影和多径衰落的影响,单认知用户检测可靠性低.基于数据融合的合作感知可以大大提高对主用户的检测概率.文中提出基于数据融合的等权重增益结合准则.仿真结果表明:当融合中心采用等权重增益结合准则时的检测性能要优于采用硬判决融合准则时的检测性能.     

双信任度加权的K秩准则频谱感知算法

基于信任度的协作频谱感知算法,可以很好地解决本地检测的隐藏终端和频谱衰落等问题。但其对于多用户的大量数据分析,缺乏高效的数据统计和融合算法,算法的检测性能有待提高。为此,提出了一种基于双信任度加权的K秩准则协作频谱感知算法。它在主用户存在与不存在两种情况下,分别采用不同的信任度加权的算法,并与K秩准则的融合策略相结合。仿真结果表明,算法在保证数据统计和融合能力的前提下,有效的提高了检测性能和感知能力。     

基于SNR比较的协作频谱感知研究

频谱感知是认知无线电中通过发现可用频率资源提高频谱利用率的关键技术。协作频谱感知能一定程度上消除多径和阴影的影响,为了进一步提高频谱检测性能,提出了一种基于SNR比较的协作频谱感知算法。在此算法中,各个认知用户将各自的本地判决结果和自身的SNR值发送到数据融合中心,通过SNR比较,对各CR用户进行筛选,选出符合算法要求的CR用户参加协作检测,进行数据融合。计算机仿真表明,该算法能有效提高检测性能,并减少判决融合的节点数量。     

Cluster based power efficient cooperative spectrum sensing under reduced bandwidth using location information

Frequency spectrum sharing between licensed primary users (PUs) and unlicensed secondary users (SUs) requires the SUs to reliably detect the spectrum occupancy. Due to multipath fading, single terminal detection is unreliable and results in a high probability of missed detection. This is solved by applying cooperative detection. However, when the number of SUs is large, the bandwidth for reporting their sensing results to the common receiver will be very huge. In this paper, we propose an improved frequency divisional cluster based cooperative spectrum sensing based on the location information which employs a censoring method to reduce the average number of sensing bits sent to the common receiver. The reduction in the number of sensing bits using proposed method in turn reduces the total transmission power of the secondary users in the cognitive network thus improving its battery life.     

Performance Evaluation of Cooperative Spectrum Sensing Scheme with Censoring of Cognitive Radios in Rayleigh Fading Channel

In this paper, the performance of cooperative spectrum sensing (CSS) with censoring of cognitive radio (CR) users in Rayleigh fading channel is analyzed. More precisely, CR users which employ energy detectors are censored depending on the quality of radio channels between them and a fusion center (FC). Each CR makes a hard decision about primary user (PU) using energy detection and transmits the information to FC using BPSK signaling if that CR user is selected to transmit. A training based channel estimator is used at the FC to estimate the complex Gaussian fading coefficients characterizing the channels between the CR users and the FC. This channel state information on fading coefficients is used for censoring the CR users. Two fusion rules such as majority logic fusion and maximal ratio combining (MRC) fusion rules are applied at the FC for estimating the performance in terms of probability of missed detection (P_m). We develop a simulation test bed for evaluating the performance of CSS scheme. Probability of missed detection has been evaluated for both perfect and imperfect channel estimation for various probabilities of false alarm (P_f), reporting and sensing channel SNR values.     

Cyclostationarity-based cooperative spectrum sensing over imperfect reporting channels

Reliable detection of weak primary user signals is a crucial problem for cognitive radio networks. To address the above issue, cooperative spectrum sensing (CSS) methods based on cyclostationary detection (CD) have been introduced in the literature. In this paper, a soft decision-based CSS method based on the second-order CD at secondary users (SUs) is proposed. The proposed scheme aims to maximize the deflection criterion at the fusion center (FC), while the reporting channels are characterized by Rayleigh fading. To this end, a fusion rule which does not require to know the noise variances of sensing channels is developed. Since the fusion rule assumes the perfect knowledge of channel state information (CSI) of reporting links, it has theoretical significance and provides an upper bound for the performance of cyclostationarity-based CSS. We have also proposed a more practical suboptimum fusion rule and studied its detection performance in the presence of uncertainties in noise variance and channel power gain estimations. Furthermore, in order to be able to evaluate the performance of the CSS, an analytic threshold estimation method has been proposed. Extensive simulation results have been illustrated the robustness of the proposed method compared to the existing cyclostationary detectors.     

Hard and softened combination for cooperative spectrum sensing over imperfect channels in cognitive radio networks

Recently, cognitive radio (CR) access has received much attention to overcome spectrum scarcity problem. Spectrum sensing methods are often used for finding free channels to be used by CR. In this paper, the problem of cooperative spectrum sensing will be investigated in CR networks over realistic channels. This problem is not clarified until now by taking into account the error effect on the decision reporting. The analytical expressions of the hard and softened one bit and two bits hard combination scheme for cooperative spectrum sensing will be derived. These expressions are investigated to compare with simulation results. The analysis and simulation results show that the performance of cooperative spectrum sensing is limited by the probability of reporting errors. Moreover, it is shown that there is a significant performance loss when a final decision regarding to primary user’s (PU) state made at the fusion depends on a set of local spectrum sensing information that are distorted by imperfect reporting channels during transmission. The probability of detection is degraded due to imperfect reporting channel by 16.5% and 12.2% with one bit hard combination and softened two bits hard combination, respectively. To reduce this performance loss, Amplify and Forward (AAF) relying mechanism will be proposed. The probability of detection is improved by 8% and 9.3% with one bit hard combination and softened two bits hard combination, respectively using AAF relaying mechanism.     

Cooperative wideband spectrum sensing based on sequential compressed sensing

Compressed sensing offers a new wideband spectrum sensing scheme in Cognitive Radio (CR). A major challenge of this scheme is how to determinate the required measurements while the signal sparsity is not known a priori. This paper presents a cooperative sensing scheme based on sequential compressed sensing where sequential measurements are collected from the analog-to-information converters. A novel cooperative compressed sensing recovery algorithm named Simultaneous Sparsity Adaptive Matching Pursuit (SSAMP) is utilized for sequential compressed sensing in order to estimate the reconstruction errors and determinate the minimal number of required measurements. Once the fusion center obtains enough measurements, the reconstruction spectrum sparse vectors are then used to make a decision on spectrum occupancy. Simulations corroborate the effectiveness of the estimation and sensing performance of our cooperative scheme. Meanwhile, the performance of SSAMP and Simultaneous Orthogonal Matching Pursuit (SOMP) is evaluated by Mean-Square estimation Errors (MSE) and sensing time.     

Scalable and Robust ANN Based Cooperative Spectrum Sensing for Cognitive Radio Networks

Cognitive radio network (CRN) supports dynamic spectrum access addressing spectrum scarcity issue experienced by today’s wireless communication network. Sensing is an important task and cooperative spectrum sensing is used for improving detection performance of spectrum. The sensing information from individual secondary users is sent to fusion center to infer a common global decision regarding primary user’s presence. Various fusion schemes for decision making are proposed in the literature but they lack scalability and robustness. We have introduced artificial neural network (ANN) at fusion center thereby achieving significant improvement in detection performance and reduction in false alarm rate as compared to conventional schemes. The proposed ANN scheme is found capable to deal with scalability of CRN with consistent performance. Further, SNR of individual Secondary user is taken into consideration in decision making at fusion center. Moreover the proposed scheme is tested against security attack (malicious users) and inadvertent errors occurring at SUs are found to be robust.     

An Innovative Cooperative Spectrum Sensing Algorithm with Non-ideal Feedback Channels and Delay Considerations

Cognitive radio (CR) is used to overcome the spectrum scarcity problem, which results from fixed allocation of wireless bands. CR allows the unlicensed secondary users to exploit the idle spectrum, which is not occupied by any licensed primary user (PU), thus increasing the overall spectrum utilization. In this paper, we first propose a simple cooperative sensing algorithm, which combines the local decision at each CR along with a group decision received from a fusion center to produce a collective decision on the existence of the PU. The performance of the algorithm is investigated over ideal and non-ideal reporting channels, from the fusion center to the CR devices, both analytically and via simulations. Furthermore, the effect of cooperation delay, which causes the decisions received by the CR device from the fusion center to be outdated, is extensively studied, both analytically and via simulations. To overcome the significant performance degradation due to the effect of delay, an extra local sensing cycle is performed at the CR side upon reception of the group decision. Results show that the proposed algorithm outperforms the conventional hard decisions technique and exhibits a comparable performance to the soft decisions approach at a considerably lower complexity. Moreover, the algorithm is shown to enjoy more robustness against reporting channel errors than the conventional hard decisions-based algorithm. Finally, the extra sensing cycle is shown to dramatically improve the performance for different delay scenarios.     

Delay QoS Guaranteed Cooperative Double-Threshold Sensing Scheme in Cognitive Radio Networks

In cognitive radio networks, cooperation can greatly improve the performance of spectrum sensing. This paper proposes a delay (QoS) quality-of-service guaranteed cooperative spectrum sensing frame structure in which secondary users (SUs) conduct spectrum sensing and data transmission concurrently over two different parts of the primary user spectrum band. A double-threshold sensing scheme is employed in the local sensing step, only the SUs with reliable sensing information are allowed to transmit their “one bit” local decisions to the fusion center. The sensing performance and the SU transmission delay are analyzed in detail in this paper. Computer simulations show that the delay QoS guaranteed cooperative double-threshold sensing scheme could not only decrease the SU transmission delay but also save the reporting overhead of the SUs compared with the conventional detection method with one threshold.