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认知无线电技术使得自组织网络节点能够充分利用空闲频谱资源,提高了传输性能。通过协作频谱感知,可有效解决由于无线信道存在阴影、噪声和衰落等情况导致的单节点感知准确性偏低。为了解决梯度算法随着协作节点数量增大后计算复杂度变高,文中提出部分梯度算法ψ-GBCS,该模型通过基于SNR的动态阈值保证了感知准确性,同时通过最佳协作节点数提高了感知效率。仿真结果表明,该模型下,综合评估系统效率和性能的J函数值提高37%,能耗降低50%,有效保证大规模认知自组网频谱感知的鲁棒性,降低了对主用户的干扰及设备功耗。 相似文献
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Labsis Lyes Teguig Djamal Lassami Nacerredine 《International Journal of Communication Systems》2023,36(11):e5502
Spectrum sensing based on detection techniques enables cognitive radio networks to detect vacant frequency bands. The spectrum sensing gives the opportunity to increase the radio spectrum channels re-utilization. However, the main challenge in spectrum sensing is the simplicity of the considered detection approach and the amount of prior information needed to make an accurate decision. This paper proposes a novel sensing technique based on the autocorrelation function. This novel approach is based on the speed of convergence to zero of all autocorrelation coefficients. This technique shows the highest probability of detection for the same probability of false alarm target at low signal-to-noise ratio (SNR) compared with many standard detection techniques. The proposed method has been implemented using GNU Radio software and SDR (software-defined radio) platforms. The experimental results show the effectiveness of the proposed method under real scenarios. 相似文献
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This paper addresses the issues on spectrum sharing in a cognitive radio network consisting of a primary user and a group of cognitive users. Each cognitive user may occupy a non‐overlapped sub‐band of the primary spectrum, but it needs to perform spectrum sensing independently before accessing the sub‐band. To reduce the complexity of spectrum sensing and thus energy consumption, this paper proposes a scheduled spectrum sensing scheme. First, we consider a single spectrum sensing scenario where only one cognitive user is elected to perform spectrum sensing, and then it broadcasts its sensing results to the other cognitive users. The scheduled spectrum sensing scheme works in both network‐centric and user‐centric ways. Next, the scheduled spectrum sensing scheme is further generalized to work in a multiple spectrum sensing scenario. The results show the effectiveness of the proposed schemes compared with the traditional schemes where all cognitive users may perform spectrum sensing at the same time. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
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Zeyang Dai Jian Liu Zhi Sun Keping Long 《International Journal of Communication Systems》2014,27(12):4226-4248
In cognitive radio networks, cooperative sensing can significantly improve the performance in detection of a primary user via secondary users (SUs) sharing their detection results. However, a large number of cooperative SUs may induce great sensing delay, which degrades the performance of secondary transmissions. In this paper, we jointly consider cooperative sensing and cognitive transmission in cognitive radio networks, aiming to achieve efficient secondary access with low sensing overhead under both the sensing time and reporting power limitations, where primary users are guaranteed to be sufficiently protected. We first propose an adaptive sensing scheme to lower the detection time while not degrading the detection probability. Then, based on the proposed adaptive sensing scheme, an efficient cognitive transmission protocol is well designed, which improves the throughput of secondary transmissions while ensuring the QoS of primary transmissions. We analyze the performance for the proposed secondary access framework in terms of misdetection probability, average detection time and normalized secondary throughput, respectively, and derive their closed‐form expressions over Rayleigh fading channels with considering the reporting errors accordingly. We also study the problems of optimizing the number of cooperative SUs to minimize the misdetection probability and average detection time, and maximize the normalized secondary throughput for proposed framework. Simulation results reveal that the proposed framework outperforms the traditional case significantly. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
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认知网络中的多用户MIMO线性协作频谱感知问题研究 总被引:1,自引:0,他引:1
研究了多用户MIMO的线性协作频谱感知问题以提高频谱检测的可靠性,推导了多用户MIMO线性协作感知系统的局部检测和全局检测策略,建立了在给定误警概率的情况下控制中心通过优化给各个用户的信号所分配的权值来最大化全局检测概率的优化模型。进一步,引入了遗传算法来求解上述全局检测优化问题的最优权值,期望能够有效降低算法在频谱感知过程中检测时间。仿真结果表明,多入多出能够明显提高协作频谱感知系统频谱检测可靠性,而遗传算法高效且稳定,相比较其他算法能够有效改善系统的检测性能。 相似文献
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Cognitive radio (CR) is a promising technology to improve the utilisation of wireless spectrum resources. Spectrum sensing is the core functionality in CR networks (CRN). When there exist malicious users (MUs) in CRN and MUs start to attack the network after accumulating reputation to some extent, the performance is deteriorated. In this paper, a scheme is proposed by employing Orthogonalized Gnanadesikan–Kettenring (OGK) to mitigate the effect of MUs without the assistance of trusted nodes, and it can improve the robustness of CRN. Simulations verify the effectiveness of the proposed scheme. 相似文献
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Sara H. Kamel Mina B. Abd‐el‐Malek Said E. El‐Khamy 《International Journal of Communication Systems》2019,32(6)
Compressive sensing is an emerging technique in cognitive radio systems, through which sub‐Nyquist sampling rates can be achieved without loss of significant information. In collaborative spectrum sensing networks with multiple secondary users, the problem is to find a reliable and fast sensing method and to secure communication between members of the same network. The method proposed in this paper provides both quick and reliable detection through compressive sensing and security through the use of deterministic chaotic sensing matrices. Deterministic matrices have an advantage over random ones since they are easier to generate and store. Moreover, it is much easier to verify whether a deterministic matrix satisfies the conditions for compressive sensing compared with random matrices, which is what makes them an interesting area of research in compressive sensing. Also, it would be a great advantage if the sensing matrices also provide inherent security, which is the motivation for using chaotic matrices in this paper, since any slight changes in the chaotic parameters result in highly uncorrelated chaotic sequences, hence entirely different sensing matrices. This makes it impossible to reconstruct the signal without proper knowledge of the parameters used to generate the sensing matrix. They can also be easily regenerated by knowing the correct initial values and parameters. Additionally, new modifications are proposed to the existing structures of chaotic matrices. The performance of chaotic sensing matrices for both existing and modified structures is compared with that of random sensing matrices. 相似文献
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Sensing the spectrum in a reliable and efficient manner is crucial to cognitive radio. To combat the channel fading suffered by the single radio, cooperative spectrum sensing is employed, to associate the detection of multiple radios. In this article, the optimization problem of detection efficiency under the constraint of detection probability is investigated, and an algorithm to evaluate the required radio number and sensing time for maximal detection efficiency is presented. To show the effect of cooperation on the detection efficiency, the proposed algorithm is applied to cooperative sensing using the spectral correlation detector under the Rayleigh flat fading channel. 相似文献
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Sercan Yalçın 《International Journal of Communication Systems》2023,36(5):e5433
The artificial intelligence-based spectrum sensing approach is extremely important in terms of effective bandwidth utilization for low power wide area networks (LPWANs) based on cognitive radio networks (CRNs). Most studies perform spectrum detection with CRNs using optimization or deep neural network methods. However, optimization-based spectrum detection approaches based on current LPWANs are scarce. For this purpose, in this study, a hybrid optimization methodology integrated with CRNs is proposed for LoRa, which is one of the most compatible LPWAN technologies in the Internet of Things (IoTs) recently. In the particle swarm optimization (PSO) part of this hybrid methodology, agent users are created so that secondary users (SUs) could use the licensed band of primary users (PUs) in cognitive radio. On the genetic algorithm side, LoRa error rates are minimized in order to further improve the performance of the proposed method. In this way, effective spectrum sensing is performed in the LoRa network. Various LoRa-CRN experiments have been carried out in the simulation environment, and the probability of detection and false alarm performances have been compared with both theoretical and proposed approaches in terms of quality estimation parameters. It is clear from the results that the proposed methods give successful results for the LoRa-CRNs. 相似文献
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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。 相似文献
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This paper analyzes the spectrum sensing performance over fading channel,in which a licensee and multiple unlicensed users coexist and operate in the licensed channel in a local area. The overall average probabilities of detection and false alarm by jointly taking the fading and the locations of all secondary users into account are derived,and a statistical model of cumulate interference is constructed. Based on the cumulate interference,a closed-form expression of outage probability at the primary user's receiver according to a specific distribution of the fading is obtained. Finally,the sensing parameters so as to minimize the total spectrum sensing error and maximize the average opportunistic throughput are obtained. It is noted that the overall average performance analysis and results here enable to benchmark the design of specific spectrum sensing algorithms. 相似文献
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In this paper,we analyze performance of cooperative spectrum sensing under counting rules when exponential model is utilized to characterize the burst nature of primary user(PU) link.Our objective is to minimize the average error probability(AEP) so that the link utilization in the considered link achieves its maximum.We derive a closed-form expression of AEP as well as the probability of interference(PoI) by classifying cognitive transmission into six events.Then,we consider the minimization of AEP over counting rules under the constraint of interference.As the solution,we develop an efficient algorithm to evaluate the optimal fusion rule.Finally,we verify our analysis in numerical results. 相似文献
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In a cognitive radio ad hoc network, there is no central authority. Hence, distributed collaborative spectrum sensing (CSS) plays a major role in achieving an accurate spectrum sensing result. However, CSS is sensitive to spectrum sensing data falsification (SSDF) attack, in which a malicious user falsifies its local sensing report before disseminating it into the network. To capture such abnormal behavior of a node, we present an approach for detecting SSDF attack based on dissimilarity score. A secondary user (SU) computes the dissimilarity score of its neighbors from the messages received from its h‐hop neighbors. Further, we also present how the proposed scheme can be used on the sequence of sensing reports to detect and isolate the malicious SUs on the fly. 相似文献
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提出多输入多输出(Multiple-Input Multiple-Output,MIMO)认知无线电系统中基于多元特征函数的频谱盲检测方法.所提方法不需要知道授权用户传输信号的先验知识,也不需要知道信道噪声的方差.通过计算次用户多天线系统接收到的信号样本向量的经验特征函数,MIMO系统中的频谱检测就转换为多元特征函数检验问题.通过度量经验特征函数与已知特征函数的距离, 实现频谱检测.在MIMO系统中,基于特征函数的频谱检测算法比现存的频谱检测方法,具有更好的性能,特别是在低信噪比、小样本条件下. 相似文献
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Haobo Qing Yuanan Liu Gang Xie 《International Journal of Communication Systems》2016,29(15):2192-2204
In this paper, we consider the problem of multiband spectrum sensing by employing smart antenna arrays at the cognitive receiver. Although energy detection is widely used for spectrum sensing in cognitive radio networks because of its simplicity and accuracy, it is severely deteriorated by the noise uncertainty. This paper introduces robust spectrum sensing techniques to circumvent this difficulty, which operate simultaneously over the total frequency channels rather than a single channel each time. To enhance the detection performance, the proposed schemes jointly utilize the information of eigenvalues and eigenvectors, signal and noise subspace components in conjunction with the likelihood functions and Gerschgorin radii. Neither subjective decision threshold setting nor the estimation of noise power is required in our schemes, making them robust to noise uncertainty. Simulations are presented to validate the performance of the proposed schemes, and the results show that our schemes can outperform other existing spectrum sensing methods. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
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A novel signal separation algorithm based on compressed sensing for wideband spectrum sensing in cognitive radio networks
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In cognitive radio networks, since cognitive terminals use a shared wideband frequency spectrum for data transmissions, they are susceptible to malicious denial‐of‐service attacks, where adversaries try to corrupt communication by actively transmitting interference signals. To address this issue, in this paper, we propose a novel signal separation algorithm based on compressed sensing, which can not only recover the entire spectrum but also separate mixed occupying signals. Specifically, the proposed algorithm is executed following three steps: (i) each cognitive terminal attempts to recover all signals over an entire wideband spectrum employing the compressed sensing technique; (ii) all cognitive terminals send their recovered signals to the fusion center where a wavelet edge detection method is adopted to locate the spectrum edges of these signals and then divide the entire spectrum into several sub‐bands; (iii) the fusion center separates its received signals on each spectrum sub‐band into different categories according to their features. Both analytical and simulation results indicate that this novel compressed‐sensing‐based algorithm can effectively separate wideband signals at a low cost and combat interference of the malicious terminals in cognitive radio networks as well. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献