认知无线电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,研究了一种基于感知信息量化的合作频谱感知模型,在此基础上,研究了感知信道信噪比、认知用户数对检测概率的影响以及感知时间、信噪比对虚警概率和吞吐量的影响,并将检测性能与软判决和硬判决比较。理论分析和仿真结果表明,该方法在每个认知用户只增加1 bit传输开销的前提下能够极大地改善检测性能,实现了频谱利用率与传输开销的较好权衡。     

利用自相关矩阵的量化合作频谱感知方法

为了改善认知无线电的频谱感知性能,提出一种基于自相关矩阵的量化合作频谱感知方法,对各认知用户的本地检测结果采用多个判决门限进行有限位的量化,在融合中心采用加权投票准则对该量化信息综合处理,得出最终判决.该方法是一种盲感知方法,不需要知道主用户信号的先验知识和噪声方差信息.具体讨论了一种2 bit量化合作频谱感知方案,并将其与传统的基于能量检测的合作频谱感知方案作比较.理论分析和仿真结果表明,该方案可以有效提高频谱感知能力.     

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。      

相关盒维数的分步合作频谱感知方法

提出一种基于分形相关盒维数的分步合作频谱感知方法,通过对信号进行自相关运算,求取其盒维数值,利用恒虚警检测得到判决门限进行判决。在所有认知用户中随机选择参与运算的认知用户,并反馈有益信息。仿真结果表明,该方法在保证检测准确率的同时,降低了认知系统合作频谱感知所带来的额外开销和频谱检测时长,减轻合作控制中心的负荷,整体上提高了认知系统的检测性能。     

优化的最佳中继协作频谱感知

在基于中继的协作频谱感知中,尽管通过引入认知中继可有效提高协作频谱感知性能,然而认知中继的引入也会带来额外的系统开销及复杂度增加问题。为了节约系统开销,本文在前期取得研究成果的基础上,进一步提出了一种基于删余的最佳中继协作频谱感知方案,只有当次用户检测到主用户信号且目标次用户的报告信道衰落严重时,才申请认知中继的协作传输,同时目标次用户将其检测到的感知信息发送到认知中继;最后,分别从检测性能和次系统可获得的容量角度对所提方案下的协作频谱感知性能进行了理论分析。分析和仿真结果表明,所提方案可以有效提高检测性能,当确保主用户受到足够保护的前提下,利用所提方案可以获得更高的次系统容量。      

基于信噪比软信息的协同频谱感知算法

针对协同频谱感知方法中假定各基站信噪比近似相同,使信噪比差异较大时检测概率性能无法得以明显提升的问题,本文提出一种在OFDM系统下,结合信噪比信息进行融合判决的协同频谱感知算法。该方法首先利用OFDM系统的循环前缀提出一种适合认知无线电系统的盲信噪比估计方法;然后,利用检测概率在信噪比-5dB~-13dB的区间内近似线性变化的特性,依据估计所得信噪比值对检测概率曲线进行软信息量化,作为各基站判决信息的置信度,从而使权重分配更加合理化,同时,相比于判决融合方法,并不明显提高传输带宽。仿真结果表明,相比与传统方法,此方法能有效利用信噪比信息,在不同信噪比环境下均有较优性能,尤其在各基站信噪比差异较大时,其性能已接近数据判决精度。      

基于信誉度的频谱感知数据融合算法

频谱感知数据融合算法对认知无线网络性能起到重要作用,目前各频谱感知算法在检测恶意节点及适应认知用户环境变化上的性能有待加强,为此,提出了一种基于认知用户过往判决记录的改进加权序贯概率比检测算法。该方法通过融合中心记录认知用户过往判决结果的符合次数,改变其信誉度,从而得到该认知用户判决结果在融合结果中所占有的加权,最终得到更为理想的判决结果。     

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。     

认知无线网络中的智能协作频谱感知机制研究

作为智能体,认知无线电应具有智能学习和智能判决的能力。为充分发掘认知用户的智能体特性,本文提出一种基于支持向量机和模糊积分的智能协作频谱感知机制。该机制将协作频谱感知模型转化成基于模糊积分的多分类器融合模型,其中每个认知用户均被看作一个独立的支持向量机分类器,单个感知周期内得到的采样数据作为分类器的输入,分类器的概率输出将被发送至融合中心,融合中心采用模糊积分算法将各分类器得到的结果进行融合并判决。该机制充分挖掘了认知用户在频谱感知阶段的“智能学习”能力和信息融合阶段的“智能判决”能力,仿真结果进一步表明,与单一的分类模型相比,本文提出的智能协作频谱感知机制具有更高的检测概率和更低的虚警概率。      

基于认知无线网络的部分用户合作频谱感知算法

在认知无线电网络中,传统的合作频谱感知算法允许所有的认知用户参与合作。但是,当参与频谱感知的用户数量较大时,就会导致系统具有较低的传输性能。因此,对一种部分认知用户参与合作频谱感知的方法进行了研究。这种方法采用不同的融合准则,在满足给定系统的检测概率和虚警概率阈值的前提下,确定参与合作感知用户的数量,从而提高系统的检测概率和能量效率,降低系统的虚警概率。     

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.     

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.     

Novel quantization‐based spectrum sensing scheme under imperfect reporting channel and false reports

In this paper, a novel sensing scheme, uniform quantization for cooperative sensing (UniQCS), that employs a uniform quantizer is proposed. UniQCS is based on energy detection and uses weight vector for global decision function. It performs better than hard decision algorithms such as majority and k‐out‐of‐n in terms of probability of detection and false alarm at the cost of a marginal increase in overhead bits under imperfect reporting channel and false reports. The probability of detection is maximized for a given probability of false alarm constraint by the proposed method. For detailed analysis, the UniQCS is compared with equal gain combiner scheme, which performs far better than hard decision algorithms, via highest bandwidth requirement. The proposed algorithm performs close to equal gain combiner. Moreover, the robustness of UniQCS to sensing error is analyzed when some nodes always report false decisions to the fusion center and the reporting channel is imperfect. For probability of false alarm equal to 0.01, performance gain of UniQCS is at least 45% compared with the other methods when there are two false reporting nodes. UniQCS performance gain is at least 15% compared with other methods for probability of reporting channel error equal to 0.001. Copyright © 2012 John Wiley & Sons, Ltd.     

A new probability decoding scheme based on genetic algorithm for FEC codes in optical transmission systems

Based on the genetic algorithm(GA),a new genetic probability decoding(GPD) scheme for forward error correction(FEC) codes in optical transmission systems is proposed.The GPD scheme can further offset the quantification error of the hard decision by making use of the channel interference probability and statistics information to restore the maximal likelihood transmission code word.The theoretical performance analysis and the simulation result show that the proposed GPD scheme has the advantages of lower decoding complexity,faster decoding speed and better decoding correction-error performance.Therefore,the proposed GPD algorithm is a better practical decoding algorithm.     

Efficient Near‐Optimal Detection with Generalized Sphere Decoder for Blind MU‐MIMO Systems

In this letter, we propose an efficient near‐optimal detection scheme (that makes use of a generalized sphere decoder (GSD)) for blind multi‐user multiple‐input multiple‐output (MU‐MIMO) systems. In practical MU‐MIMO systems, a receiver suffers from interference because the precoding matrix, the result of the precoding technique used, is quantized with limited feedback and is thus imperfect. The proposed scheme can achieve near‐optimal performance with low complexity by using a GSD to detect several additional interference signals. In addition, the proposed scheme is suitable for use in blind systems.     

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.     

一种能效优先的认知无线电模仿主用户攻击防御策略设计与性能分析

研究了一种能效优先的认知无线电PUEA防御策略并对其进行了性能分析.以PUEA存在时CSS能效作为目标函数,以CSS安全检测性能作为约束条件,从而构建一个安全的CSS系统模型进而求解该优化问题,实现保障能量有效性的安全频谱检测.在CSS中,融合中心以K秩准则(K-out-of-N准则)作为全局判决准则,保证能效最大化时得到最佳门限K和最佳认知用户数N.通过与最大比合并(MRC)准则下的安全CSS进行比较,所提PUEA防御策略在保证系统能效的同时提高了系统的检测性能,即所提PUEA防御策略可以有效折中能效与检测性能.数值仿真结果表明,所提策略不受PUE干扰功率影响,对于PUEA攻击具有较高的顽健性.     

Adaptive joint maximum‐likelihood detection and minimum‐mean‐square error with successive interference canceler over spatially correlated multiple‐input multiple‐output channels

We develop an efficient hard detector for multiple‐input multiple‐output (MIMO) channels, which adaptively combines maximum‐likelihood detection (MLD) and minimum‐mean‐square error with a successive interference canceler together. Unlike the conventional joint combination scheme, which may suffer from considerable degradation in bit‐error‐rate (BER) performance over correlated channels and where only one data stream is detected by MLD, our proposed scheme adaptively controls the number of data streams to be detected by MLD based on an analytical characterization of reliability for the detection. Simulation results illustrate that near‐optimal BER performance can be obtained at much lower computational complexity by the proposed method as compared with existing techniques, regardless of the spatial correlation of the MIMO channels. Copyright © 2012 John Wiley & Sons, Ltd.     

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。