Optimization algorithm of periodical cooperative spectrum sensing in cognitive radio

To decrease the interference to the primary user (PU) and improve the detected performance of cognitive radio (CR), a single‐band sensing scheme wherein the CR periodically senses the PU by cooperative spectrum sensing is proposed in this paper. In this scheme, CR first senses and then transmits during each period, and after the presence of the PU is detected, CR has to vacate to search another idle channel. The joint optimization algorithm based on the double optimization is proposed to optimize the periodical cooperative spectrum sensing scheme. The maximal throughput and minimal search time can be respectively obtained through the joint optimization of the local sensing time and the number of the cooperative CRs. We also extend this scheme to the periodical wideband cooperative spectrum sensing, and the joint optimization algorithm of the numbers of the sensing time slots and cooperative CRs is also proposed to obtain the maximal throughput of CR. The simulation shows that the proposed algorithm has lower computational quantity, and compared with the previous algorithms, when SNR = 5 dB, the throughput and search time of the proposed algorithm can respectively improve 0.3 kB and decrease 0.4 s. The simulation also indicates that the wideband cooperative spectrum sensing can achieve higher throughput than the single‐band cooperative spectrum sensing. Copyright © 2012 John Wiley & Sons, Ltd.     

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.     

Sensing‐throughput tradeoff for cooperative multiple‐input single‐output cognitive radio

In this paper, we propose a new cooperative multiple‐input single‐output (MISO) cognitive radio (CR) system, which can use some of the antennas to transmit its data and the others to help to transmit the data of the primary user (PU) by performing cooperative communication if the presence of the PU is detected through the cooperative spectrum sensing. A new cooperative sensing‐throughput tradeoff model is proposed, which maximizes the aggregate rate of the CR by jointly optimizing sensing time and spatial sub‐channel power, subject to the constraints of the aggregate rate of the PU, the false alarm and detection probabilities, the aggregate interference to the PU and the aggregate power of the CR. Simulation results show that compared with the conventional scheme, the proposed cooperative scheme can achieve the larger aggregate rate of the CR, while keeping the aggregate rate of the PU invariable with the increasing of the interference. Copyright © 2013 John Wiley & Sons, Ltd.     

Fault-Tolerant Cooperative Spectrum Sensing Scheme for Cognitive Radio Networks

In order to solve the uncertainty resulting from shadowing effect and resist the attack from malicious cognitive radio (CR) users, we propose a fault-tolerant cooperative spectrum sensing scheme for CR networks, where an energy detection-based local spectrum sensing is performed at each CR user, a coefficient is used to weight each CR user’s sensing result, a linear weighted fusion process is performed at the fusion center (FC) to combine received sensing results. For a fault-tolerant cooperative spectrum sensing scheme, the most important issue is to distinguish whether the CR user is reliable or not. In this paper, a reputation-based cooperative mechanism is presented to alleviate the influence of the unreliable sensing results from CR users suffering shadowing and the false sensing data from malicious CR users on the detection result at the FC. In proposed fault-tolerant cooperative scheme, each cooperative CR user has a reputation degree which is initialized and adjusted by the FC and used to weight the sensing result from the corresponding user in the fusion process at the FC. And then, two reputation degree adjusting methods are presented to manage the reputation degree of each CR user. Simulation results show that the proposed scheme can not only weaken the harmful influence caused by malicious CR users, but also alleviate the corrupted detection problem resulting from destructive channel condition between the primary transmitter and the CR user. Moreover, the detection performance of the fault-tolerant cooperative scheme, which has a feasible computational complexity and needs no instantaneous SNRs, is close to that of the optimal scheme.     

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.     

The effect of Weibull fading channel on cooperative spectrum sensing network using an improved energy detector

This paper analyses the performance of proposed cooperative spectrum sensing (CSS) network in Weibull fading environment. First, we have derived the novel analytic expressions for probabilities of missed detection and false alarm in Weibull fading channel, assuming an improved energy detector (IED), selection combining diversity scheme and multiple antennas at each cognitive radio (CRs). Next, performance is analyzed using complementary receiver operating characteristics curves, total error rate, average channel throughput, and network utility function curves for the proposed CSS network. The optimal performance of CSS network is achieved by optimizing the CSS network parameters. The closed form of expressions for the optimum value of number of CRs, arbitrary power of received signal, and detection threshold at each CR are derived using OR-Rule and AND-Rule at fusion center (FC). The average channel throughput and network utility function analysis are evaluated using \(k=1+n\) and \(k=N-n\) fusion rules at FC. Finally, the impact of several network parameters such as, multiple antennas at each CR (M), number of CRs (N) in CSS network, Weibull fading parameter (V), arbitrary power of received signal (p), and sensing channel SNR (\({\bar{\gamma }})\) on the performance of proposed CSS network are investigated using the simulation results. The performance comparison between conventional energy detector and an IED has been highlighted with the simulations.     

基于能量约束的协作频谱感知算法研究

为了实现绿色节能认知通信的目标,针对协作感知和传输过程中的能量消耗问题,提出了一种基于能量约束的集中式协作频谱感知算法。建立了系统检测寿命最大化的频谱感知模型,对其进行了详细分析,给出了检测寿命最大化对应参数的搜索方法。仿真结果显示,该方法可以在满足检测精度的条件下有效延长认知网络的检测寿命,并提高低信噪比用户参与协作的几率。     

Distributed Cooperative Wideband Spectrum Sensing Algorithm Based on Subspace Methods

We present a novel distributed cooperative spectrum sensing algorithm from compressive sampling in wideband cognitive radio (CR) networks. Each CR utilizes compressive sampling to reduce data acquisition costs. A subspace method is then adopted to directly detect occupied channels without reconstructing the sparse spectrum. To obtain the spatial diversity gain, global signal subspace is estimated by the distributed projection approximation subspace tracking (DPAST) algorithm in which the CRs exchange information locally and cooperate without the need for a fusion center. Then, the orthogonality property of the signal subspace and noise subspace can be exploited to find spectral support to complete the spectrum sensing. We study the convergence behavior of the DPAST algorithm and evaluate the performance of spectrum sensing. Simulation results indicate that the DPAST can effectively estimate the global signal subspace, and the proposed compressed wideband spectrum sensing scheme performs better than spectrum sensing at a single CR.     

Optimization of 2‐stage cooperative spectrum for cognitive radio networks using multi‐antenna energy detectors

Cooperative spectrum sensing, a kind of spectrum sensing scheme in cognitive radio (CR), uses multiple CR relays. To increase performance, this study uses multi‐antenna CR relays and beam‐forming reception. The required bandwidth for reporting channels in cooperative spectrum sensing is crucial. Two‐stage cooperative spectrum sensing is proposed to increase performance without increasing the required bandwidth. The cooperative spectrum sensing is also optimized to allow the CR networks to facilitate the best decision‐making. This study determines the detection performance when beam‐forming reception is used. Numerical simulations are used to validate the effectiveness of the method. It is shown that beam‐forming reception outperforms square‐law combining (SLC) for low SNR values. This study proposes a 2‐stage cooperative spectrum sensing method, which uses multi‐antenna CR relays and beam‐forming reception. The cooperative spectrum sensing is also optimized to allow the CR networks to facilitate the best decision‐making. Numerical simulations are used to validate the effectiveness of the method.     

基于随机矩阵理论的协作频谱感知

认知无线电频谱共享技术在新一代无线通信网络中具有广泛的应用前景,频谱感知是其中最重要的环节。该文提出了一种新的在多认知用户环境中,基于大维随机矩阵理论的协作频谱感知算法。充分利用随机矩阵的渐近谱分布特性及小样本下最大特征值收敛特性来提高感知性能。理论分析和仿真结果均表明,新算法性能明显优于同类算法和典型的能量检测算法。     

Ad Hoc认知网络中基于梯度算法的协作压缩频谱感知方法

ad hoc认知网络(CRAHNs)比起传统ad hoc网络有很多优势,如分布式多跳结构及动态变化的网络拓扑等。频谱感知是认知无线电技术的基础,采用压缩感知方法以低于奈奎斯特采样率的速率来获得较好的重构信号,同时可减轻数字处理设备的压力。本文使用多跳模型,每个认知用户感知的频谱不仅包括主用户的主频谱,也包括认知用户自身收到其他认知用户干扰的更新频谱。由于具有动态特性的ad hoc网络缺少融合中心,所以本文中提出一种基于梯度的分布式协作感知算法。该算法基于能量检测,具有可靠的感知性能和较少的能量消耗,并能快速收敛。仿真实验验证了算法的有效性。      

Throughput analysis in censoring-based cooperative cognitive radio network with energy harvesting

An energy harvesting (EH) and cooperative cognitive radio (CR) network (CRN) is studied in this paper where CR users transmit data through a primary user (PU) channel if the channel remains idle, else an optimal number CRs helps in transmission of PU. To achieve the optimum number of CRs (ONCR) involved in cooperation, a novel scheme based on a combination of channel censoring and total error is proposed. The performance of the proposed scheme is investigated under RF harvesting scenario. The EH is dependent on sensing decision and a CR source harvests energy from PU's RF signal. The harvested energy (HE) is split into two parts: One part is used by the CR network (CRN) for its own transmission, and the other part is used for supporting PU. The effect of the energy allocation factor on total throughput is also investigated. New expressions for optimal number of CRs and throughput are developed. The effect of network parameters such as sensing time, censoring threshold, and energy allocation parameter (EAP) on throughput is investigated. Impact of distance between nodes is also studied.     

Sequential opportunistic spectrum access with imperfect channel sensing

In this paper, we exploit channel diversity for opportunistic spectrum access (OSA). Our approach uses instantaneous channel quality as a second criterion (along with the idle/busy status of the channel) in selecting channels to use for opportunistic transmission. The difficulty of the problem comes from the fact that it is practically infeasible for a cognitive radio (CR) to first scan all channels and then pick the best among them, due to the potentially large number of channels open to OSA and the limited power/hardware capability of a CR. As a result, the CR can only sense and probe channels sequentially. To avoid collisions with other CRs, after sensing and probing a channel, the CR needs to make a decision on whether to terminate the scan and use the underlying channel or to skip it and scan the next one. The optimal use-or-skip decision strategy that maximizes the CR’s average throughput is one of our primary concerns in this study. This problem is further complicated by practical considerations, such as sensing/probing overhead and sensing errors. An optimal decision strategy that addresses all the above considerations is derived by formulating the sequential sensing/probing process as a rate-of-return problem, which we solve using optimal stopping theory. We further explore the special structure of this strategy to conduct a “second-round” optimization over the operational parameters, such as the sensing and probing times. The aggregate throughput performance when a network of CRs coexist with primary radios is evaluated under homogeneous and heterogeneous spectrum environments, respectively. We show through simulations that significant throughput gains (e.g., about 100%) are achieved using our joint sensing/probing scheme over the conventional one that uses sensing alone.     

基于加权平均一致算法的宽带压缩频谱感知

在认知无线电(CR)网络中进行频谱共享接入,首要的任务是进行频谱感知,并发现频谱空洞。基于认知无线网络中信号频域的固有稀疏性,本文结合了压缩感知(CS)技术与加权平均一致(weighted average consensus)算法,建立了分布式宽带压缩频谱感知模型。频谱感知分为两个阶段,在感知阶段,各个CR节点对接收到的主用户信号进行压缩采样以减少对宽带信号采样的开销和复杂度,并做出本地频谱估计;在信息融合阶段,各CR节点的本地频谱估计结果以分布式的方式进行信息融合,并得到最终的频谱估计结果,获得分集增益。仿真结果表明,结合压缩感知与加权平均一致算法增强了频谱感知的性能,比在相同的CR网络中使用平均一致算法时有了性能上的提升。      

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。     

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.     

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.     

Cooperative spectrum sensing for cognitive radio networks in the presence of smart malicious users

Cognitive radio (CR) signaling imposes some threats to the network. One of these common threats is commonly referred to as primary user emulation attack, where some malicious users try to mimic the primary signal and deceive secondary users to prevent them from accessing vacant frequency bands. In this paper, we introduce a smart primary user emulation attacker (PUEA) that sends fake signals similar to the primary signal. We assume a smart attacker, in the sense that it is aware of its radio environment and may choose different transmission strategies and then, we compare it to an always present attacker. In the proposed smart attacker strategy, the occurrence of fake signal is adjusted according to the primary user activity. First, we investigate the received signal at the CR users under such attackers. Then, we formulate and derive cooperative spectrum sensing (CSS) rules for a cognitive network operating in the presence of a PUEA and propose a new spectrum sensing scheme based on energy detection. Simulation results show that our proposed method can mitigate the destructive effect of PUEA in spectrum sensing, compared to conventional energy detection spectrum sensing.     

Cross‐layer optimization for full‐duplex cognitive radio network with cooperative spectrum sensing

In this paper, the cross‐layer optimal design of multihop ad hoc network employing full‐duplex cognitive radios (CRs) is investigated. Firstly, the analytical expressions of cooperative spectrum sensing performance for multihop CR networks over composite fading channels are derived. Then, the opportunistic throughput and transmit power of CRs are presented based on the derivation of false alarm and missed detection probability. Finally, a multiobjective optimization model is proposed to maximize the opportunistic throughputs and minimize the transmitting power. Simulation results indicate that Pareto optimal solution of sensing duration, decision threshold, and transmit power can be achieved by cross‐layer multiobjective optimization, it can balance the conflicts between different objective functions and reap the acceptable outcomes for multihop CR network.     

SNR-based weighted cooperative spectrum sensing in cognitive radio networks

Cooperative spectrum sensing (CSS) is an approach to confront fading environment. However, in conventional cooperative spectrum sensing (CCSS), the difference among the secondary users (SUS) is ignored when SUS suffer from different fading. In this article, a signal-to-noise ratio (SNR)-based weighted spectrum sensing scheme is proposed to improve the sensing performance. The sensing performance of the weighted spectrum sensing scheme is then derived. Considering the minor contribution of the SUS with small weighted factor, a selective CSS scheme is proposed, where SUS with low SNR are not selected into cooperative spectrum sensing. The simulation results confirm the analytical results. And the performance of weighted scheme is better than that of conventional schemes. In the case where the SNR of SUS are randomly distributed, the performance of selective scheme is almost the same as the weighted scheme while the number of cooperative SUS is reduced to save the consumption of system resource in cooperation with little additional complexity.