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。     

Cooperative Spectrum Sensing Scheme with Hard Decision Based on Location Information in Cognitive Radio Networks

Without an efficient way to achieve the reliability of the decision, the implementation of weighted data fusion is limited in the hard decision combination for cooperative spectrum sensing. To address this problem, a new cooperative spectrum sensing scheme based on the location information of the primary user (PU) and cognitive radio (CR) is proposed. In the new scheme, depending on the location information, the channel condition between the PU and each CR is obtained at the fusion center (FC), with which the local sensing reliability is first achieved. Then we calculate the transmission reliability between the CR and FC. Based on both the local sensing reliability and the transmission reliability, the combining weighting factor is determined for optimal data fusion. On the basis of this proposed scheme, we study the global sensing false alarm and detection probabilities, derive the expressions to obtain the optimal local sensing threshold, and perform an error analysis that demonstrates the impact of imperfect channel knowledge. Using both analytical and simulation methods, we find that the proposed scheme achieves better performance compared with the conventional logical fusion rules in the hard decision combination for cooperative spectrum sensing.     

认知无线电中基于加权硬判决的协作频谱感知算法

Weighted one bit hard combination for cooperative spectrum sensing is proposed in this paper. Two thresholds are adopted to divide the possible energy value into three weighted regions.If the energy value falls into the corresponding region, it will be judged as “1”, no information or “0”. When the probability of false alarm is constrained to be constant, the objective is to maximize the probability of detection. The optimization problem is simplified by separating the weight of the middle region into several intervals. Simulation results show that the sensing performance of the proposed scheme is much better than that of the traditional one bit hard combination scheme and almost the same as that of the equal gain combination (EGC) scheme. Moreover, compared with the traditional one bit hard combination, fewer average sensing bits are required to transmit to the data fusion center with the proposed method.     

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.     

模拟人群信任和决策机制的协作频谱感知方法

通过模拟人群内部的信任和决策机制,针对多用户的频谱协作感知一致性问题,提出了一种分布式算法。该算法首先通过网络的历次协作过程预测出各感知用户的动态可信值,据此产生用户的相对可信值,并结合决策机制使得用户之间进行数据交互,随着数据的可信、迭代交互,所有用户状态将趋于一致,最后通过判定算法得出最终结果。算法充分考虑了实际环境中各用户频带感知能力的不平衡性,而且各次级用户只需要进行少量局部数据交换即可实现协作感知,与传统的OR-rule、1-out-of-N rule以及普通迭代法有较大区别。对3种数据篡改攻击进行了分析,并在预测算法的基础上提出了相应的安全策略。理论分析与仿真结果表明,新算法在准确性和安全性上均优于传统合作频谱感知算法,能显著提高频谱感知准确率,同时兼具较强的防攻击能力。     

认知无线电中基于感知信息量化的合作频谱感知

针对认知无线电频谱感知性能的提高与传输开销的矛盾,本文提出了一种基于感知信息量化的合作频谱感知方案。该方法对各认知用户的本地检测结果采用3个判决门限进行2比特位的量化,在融合中心处对量化信息加权处理后,得到最终主用户是否存在的判决。本文详细研究了采用该方案的检测概率,虚警概率和吞吐量,理论分析和仿真结果表明,该方法在每个认知用户只增加1bit传输开销的前提下能够极大的改善检测性能,实现了检测性能与传输开销的较好权衡。     

A collaborative spectrum sensing scheme using fuzzy comprehensive evaluation in cognitive radio

Cognitive Radio (CR) is a promising technology to solve the challenging spectrum scarcity problem.However,to implement CR,spectrum sensing is the groundwork and the precondition.In this paper,a collaborative spectrum sensing scheme using fuzzy comprehensive evaluation is proposed.The final sensing decision of the proposed scheme is based on the combination of distributed sensing results of different Secondary Users (SUs).To improve the reliability of the sensing decision,the combination procedure takes into account the credibility of each SU,which is evaluated using fuzzy comprehensive evaluation.The effect of the presence of malicious SUs and malfunctioning SUs on the performance of the proposed scheme is also investigated.The efficiency of the scheme is validated through analysis and simulation.     

Compressive network coding for error control in wireless sensor networks

Since the observed signals of nearby sensors are known to be correlated, this paper firstly investigates the connection between network coding and compression concept of compressed sensing and then makes an in-depth combination between these two powerful concepts for error control in wireless sensor networks. Thus, a joint scheme is developed to achieve the maximum gain by exploiting the temporal and spatial correlations simultaneously. This scheme overcomes drawbacks of network coding theory by injecting the corresponding distributed compressed sensing concept into network coding, i.e., the scheme possesses good compression gain and graceful degradation of precision in the reconstruction process. Meanwhile, it can tolerate finite erasures and errors as well as reconstruct the original information as precise as possible when the rank of error matrix (induced by erasures and errors) doesn’t exceed the upper boundary. Finally, the reliability analysis and numeric results show that the compressive network coding scheme (i.e., the joint scheme) outperforms the conventional network coding scheme in robustness and performance.     

基于证据折扣优化DSmT的协同频谱感知器

协同频谱感知器通过充分利用多个认知无线电用户的空间分集增益,对抗单用户深度衰落和阴影效应问题,降低了感知系统对本地感知用户的灵敏度要求,减少由于单用户检测不确定性带来的系统误判。利用D-S方法进行协同频谱感知,通过在本地提取置信指派,再上传至融合中心进行证据推理与判决,占用较窄的控制信道带宽,达到优于传统方法的检测性能,如“或”、“与”和“最优融合”感知方法。但低信噪用户带来的冲突数据会限制D-S方法性能,使其信噪鲁棒性较差。本文首先定义感知用户基本置信指派函数,基于DSmT提出证据折扣优化 DSmT协同频谱感知器。该感知器根据不同认知用户数据的可靠性,对其置信指派函数进行折扣,加强高可靠性数据对融合结果的贡献,降低不可靠数据对融合结果的干扰,有效解决冲突数据下的协同频谱感知信息融合问题。仿真结果表明,证据折扣优化DSmT协同频谱感知器具有良好的检测性能和信噪比鲁棒性。      

A novel cooperative spectrum sensing scheme based on virtual soft information fusion

In cognitive radio (CR), the performance of hard information fusion (HIF) strategy for cooperative sensing will deteriorate when cooperative CR user are not uniformly reliable. To deal with this problem, this paper proposed a novel virtual soft information fusion (VSIF) strategy which uses expectation for primary users (PU) presence probability to replace the local sensing decision of each user in the information fusion. Compared with the HIF-based scheme, VSIF-based sensing scheme keeps the advantages of low data transmission in HIF-based scheme, and modifies the way of information fusion at the fusion center to achieve better performance when the user sensing reliability is non-uniform. Simulation shows VSIF strategy has significant superiority on the missing detection probability over HIF in the scenarios of non-uniform user reliability.     

基于OFDM符号宽度的循环平稳频谱感知方法

该文提出一种新的基于OFDM符号宽度的感知方法。该方法首先对接收到的每个OFDM符号在其符号周期内进行循环自相关函数的估计,然后利用多元统计理论计算判决量和判决门限,最后将判决量和判决门限进行比较从而得到判决结果。该方法是非参数化的,因而能够在噪声不确定的情况下有效工作,并且该方法能够极大简化目前循环平稳感知类算法的复杂度而只有细微的性能损失。此外,该文接着又提出一个非参数化多天线线性加权合并感知方法。仿真结果表明,所提合并方法通过合理地非参数化优化加权系数,与传统循环平稳感知方法相比,在复杂度显著降低的同时,性能几乎与传统循环平稳感知方法一致。     

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.     

授权用户信号随机到达时基于双门限的多用户合作频谱感知方法

针对认知无线电系统中可能出现的授权用户信号随机到达时的频谱感知问题,提出了一种基于双门限的多用户合作频谱感知方法.首先在本地判决时采用高低双门限的方式,如果判决量大于高门限就判1,小于低门限判0,在两个门限之间就把判决量直接发送给融合中心,融合中心将直接收到的判决量进行软判决合并,软判决的结果再与其他硬判决的结果进行"OR原则"的硬判决合并,从而得到最终的判决结果.仿真表明所提方法的性能比传统"OR原则"硬判决合并方案要好,仅仅略逊于传统等增益软判决合并方案,但是能大量节省认知网络中的传输比特数.     

基于压缩感知解码的网络编码技术

证明了随机网络编码的传输矩阵具有压缩感知观测矩阵的性质,提出了一种基于随机编码和压缩感知的网络编码方案,该方案利用了压缩感知求解欠定方程组的优点。在该方案中,随机网络编码的误码率可以依靠信息的稀疏性而降低。如果信息足够稀疏,那么网络的容量甚至可以超过限定了网络编码容量上界的最大流-最小割定理的理论值。给出了误码率的理论上界,仿真结果表明该方案可以达到较好的性能。     

D-S证据理论在认知无线电中的应用

针对认知无线电（CR）中协作频谱感知时信息不确定性带来严重的性能影响,在协作开销允许的情况下,人们渴望得到感知增益很高的协作感知方案。由于D-S证据理论在决策系统中处理不确定性信息时能获得令人满意的性能,使得其在认知无线电中的应用会起很重要作用。一种基于D-S证据理论的协作频谱感知新方案被提出和发展。该方案能有效地提高...     

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。     

基于OFDM循环前缀的认知无线电频谱侦听方法

针对OFDM系统的特点,介绍了一个新的频谱侦听方法,它充分利用了正交频分复用符号中的循环前缀和空闲时间来提高侦听精度。通过建立OFDM收发双方的信号模型,以能量检测的方法为基础,分析并仿真了这种新方法的性能,结果表明,与传统的只利用空闲时间的侦听方法相比,提出的方法能有效提高侦听精度。     

一种支持多星多任务遥感卫星地面系统综合处理的运行控制技术

该文以遥感卫星地面系统信息处理的运行控制需求为背景,在分析现有多种技术方案的基础上,提出了一种基于消息队列中间件IBM WebSphere MQ的地面系统信息处理运行控制方案,并进行了成功的工程实践,指出该技术方案可直接应用于多星多任务遥感卫星星座地面系统综合处理的运行控制。     

Efficient Spectrum Sensing with Minimum Transmission Delay in Cognitive Radio Networks

In cognitive radio (CR) networks, the secondary users (SUs) need to find idle channels via spectrum sensing for their transmission. In this paper, we study the problem of designing the sensing time to minimize the SU transmission delay under the condition of sufficient protection to primary users (PUs). Energy detection sensing scheme is used to prove that the formulated problem indeed has one optimal sensing time which yields the minimum SU transmission delay. Then, we propose a novel cooperative spectrum sensing (CSS) framework, in which one SU’s reporting time can be used for other SUs’ sensing. The analysis focuses on two fusion strategies: soft information fusion and hard information fusion. Under soft information fusion, it is proved that there exists one optimal sensing time that minimizes the SU transmission delay. Under hard information fusion, for time varying channels, the novel multi-slot CSS is derived. The performance of SU transmission delay is studied in both perfect and imperfect reporting channels. Some simple algorithms are derived to calculate the optimal sensing settings that minimize the SU transmission delay. Computer simulations show that fundamental improvement of delay performance can be obtained by the optimal sensing settings. In addition, the novel multi-slot CSS scheme shows a much lower transmission delay than CSS based on general frame structure.     

Secure centralized spectrum sensing for cognitive radio networks

Spectrum utilization becomes more and more important while new communication techniques keep increasing and the spectrum bands remain finite. Cognitive radio is a revolutionary technology to make use of the spectrum more effectively. In order to avoid the interference to the primary user, spectrum sensing must be sensitive and reliable. Cooperative spectrum sensing (CSS) is one of the ways to increase the reliability of spectrum sensing. The information fusion technique is a key component of CSS. In this paper, we proposed a novel fusion scheme based on spatial correlation technique. We utilize geographical information with reputational weights to propose a two-level fusion scheme called secure centralized spectrum sensing (SCSS). The simulation results show that as the attackers present high density aggregation at some areas, the correct sensing ratio of SCSS is increasing as well even when the number of attackers is very large.