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Artykuły w czasopismach na temat „Cooperative Spectrum Sensing (CSS)”

Autor: Grafiati

Data publikacji: 2 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Tan, Youheng, and Xiaojun Jing. "Cooperative Spectrum Sensing Based on Convolutional Neural Networks." Applied Sciences 11, no. 10 (2021): 4440. http://dx.doi.org/10.3390/app11104440.

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Cooperative spectrum sensing (CSS) is an important topic due to its capacity to solve the issue of the hidden terminal. However, the sensing performance of CSS is still poor, especially in low signal-to-noise ratio (SNR) situations. In this paper, convolutional neural networks (CNN) are considered to extract the features of the observed signal and, as a consequence, improve the sensing performance. More specifically, a novel two-dimensional dataset of the received signal is established and three classical CNN (LeNet, AlexNet and VGG-16)-based CSS schemes are trained and analyzed on the propose

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Dobaria, Ankit D., and Dr Vishal S. Vora. "Performance Evaluation of DCSS using Two Level 1-Bit Hard Decision Strategies over TWDP Fading Channel." International Journal of Electrical and Electronics Research 10, no. 4 (2022): 1064–70. http://dx.doi.org/10.37391/ijeer.100450.

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The spectrum sensing method's dependability is greatly influenced by two of the most crucial factors, including various fading channels and nearby wireless users. Multipath fading, buried terminals, and shadowing are just a few of the challenges encountered by users of non-cooperative spectrum sensing systems. Cooperative spectrum sensing approach gives a remedy for this issue. With the use of the common receiver, CSS permits the user to detect the spectrum. Additionally, it has been separated into distributed CSS (D-CSS) and centralized CSS (C-CSS). By using particular rules to identify the p

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Wu, Qingying, Benjamin K. Ng, and Chan-Tong Lam. "Energy-Efficient Cooperative Spectrum Sensing Using Machine Learning Algorithm." Sensors 22, no. 21 (2022): 8230. http://dx.doi.org/10.3390/s22218230.

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Cognitive Radio (CR) is a practical technique for overcoming spectrum inefficiencies by sensing and utilizing spectrum holes over a wide spectrum. In particular, cooperative spectrum sensing (CSS) determines the state of primary users (PUs) by cooperating with multiple secondary users (SUs) distributed around a Cognitive Radio Network (CRN), further overcoming various noise and fading issues in the radio environment. But it’s still challenging to balance energy efficiency and good sensing performances in the existing CSS system, especially when the CRN consists of battery-limited sensors. This

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Gul, Noor, Su Min Kim, Jehad Ali, and Junsu Kim. "UAV aided virtual cooperative spectrum sensing for cognitive radio networks." PLOS ONE 18, no. 9 (2023): e0291077. http://dx.doi.org/10.1371/journal.pone.0291077.

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Cooperative spectrum sensing (CSS) involves multiple secondary users (SUs) reporting primary user (PU) channel sensing states to the fusion center (FC). However, the high overheads associated with multi-user CSS impose power limitations that limit its usefulness in unmanned aerial vehicle (UAV) networks. To address this challenge, we propose a virtual CSS, where a single UAV conducts CSS while following a circular flight trajectory in the air. The novelty of our approach is presenting a working frame structure for the UAV flight, including sensing and data transmission periods with further div

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Dobaria, Ankit D., and Vishal S. Vora. "Efficacy of Decentralized CSS Clustering Model Over TWDP Fading Scenario." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 4s (2023): 317–24. http://dx.doi.org/10.17762/ijritcc.v11i4s.6574.

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Cognitive Radio technology, which lowers spectrum scarcity, is a rapidly growing wireless communication technology. CR technology detects spectrum holes or unlicensed spectrums which primary users are not using and assigns it to secondary users. The dependability of the spectrum-sensing approach is significantly impacted from two of the most critical aspects, namely fading channels and neighboring wireless users. Users of non-cooperative spectrum sensing devices face numerous difficulties, including multipath fading, masked terminals, and shadowing. This problem can be solved using a cooperati

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Jiang, Haibin, Zhiyong Yu, Jian Yang, and Kai Kang. "Throughput-Oriented Full-Duplex Cognitive Radio Network Parameter Optimization." International Journal of Antennas and Propagation 2022 (January 4, 2022): 1–8. http://dx.doi.org/10.1155/2022/4056645.

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Full-duplex cooperative spectrum sensing (FD-CSS) is an important research field in the field of spectrum sensing. In the FD-CSS network, the secondary user (SU) senses the usage status of the authorized spectrum by the primary user (PU) through the sensing channel and then reports the perceived data to the fusion center (FC) through the reporting channel. The FC makes a comprehensive judgment after summarizing the data through the fusion algorithm. In the secondary network with SU, throughput is an important index to measure the performance of the network. Taking throughput as the optimizatio

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Sharma, Krishnakant, and Meenakshi Awasthi. "Cooperative Spectrum Sensing with Amplify and Forward Scheme in CRNs." Journal of Physics: Conference Series 2570, no. 1 (2023): 012031. http://dx.doi.org/10.1088/1742-6596/2570/1/012031.

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Abstract Recent research has identified cognitive radio (CR) as a possible solution for increasing spectrum usage by allowing secondary access to unlicensed bands. Having no interference with the primary system is a need for this secondary access. Due to this requirement, spectrum sensing becomes a crucial component of cognitive radio systems. The ease and effectiveness of energy detection make it an appealing technique among popular spectrum sensing techniques. The uses of the available radio network spectrum, finite and important resources, have been severely constrained by the rising demand

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Ali, Mohsin, and Haewoon Nam. "Optimization of Spectrum Utilization in Cooperative Spectrum Sensing." Sensors 19, no. 8 (2019): 1922. http://dx.doi.org/10.3390/s19081922.

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This paper presents an analytical framework for the probability of spectrum hole utilization (PSHU) of a cognitive radio system with soft cooperative spectrum sensing (CSS) under a practical consideration of fixed frame structure. In practical systems, the length of a time-frame is generally fixed, where the time-frame consists of sensing, reporting, and transmission durations. Thus, increasing sensing and reporting time duration in cooperative spectrum sensing improves the probability of successful detection of the primary user’s (PU) presence or the absence but reduces transmission time dura

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R, Aswatha, Seethalakshmi V, Murugan K, Sathishkumar N, Reethika A, and Gunanandhini S. "Implementation of cooperative spectrum sensing using cognitive radio testbed." Indian Journal of Science and Technology 13, no. 13 (2020): 1355–66. https://doi.org/10.17485/IJST/v13i13.94.

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Abstract <strong>Objectives:</strong> To implement energy detection and eigenvalue based cooperative spectrum sensing in NI-USRP hardware platform and to obtain its performance.Cooperative spectrum sensing is to be implemented using O and AND fusion rules. <strong>Methodology:</strong> The hardware is implemented using one primary user transmitter and two cognitive radio users. The implementation is done using LABVIEW and detection performance is analyzed. In cooperative spectrum sensing (CSS), CR system shares its own sensing information with other sensing nodes and utilizes th

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Gul, Noor, Muhammad Sajjad Khan, Junsu Kim, and Su Min Kim. "Robust Spectrum Sensing via Double-Sided Neighbor Distance Based on Genetic Algorithm in Cognitive Radio Networks." Mobile Information Systems 2020 (July 23, 2020): 1–10. http://dx.doi.org/10.1155/2020/8876824.

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In cognitive radio networks (CRNs), secondary users (SUs) can access vacant spectrum licensed to a primary user (PU). Therefore, accurate and timely spectrum sensing is vital for efficient utilization of available spectrum. The sensing result at each SU is unauthentic due to fading, shadowing, and receiver uncertainty problems. Cooperative spectrum sensing (CSS) provides a solution to these problems. In CSS, false sensing reports at the fusion center (FC) received from malicious users (MUs) drastically degrade the performance of cooperation in PU detection. In this paper, we propose a robust s

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Balakumar, D., and Nandakumar Sendrayan. "Enhance the Probability of Detection of Cooperative Spectrum Sensing in Cognitive Radio Networks Using Blockchain Technology." Journal of Electrical and Computer Engineering 2023 (December 18, 2023): 1–13. http://dx.doi.org/10.1155/2023/8920243.

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Cognitive radio (CR) is the best way to improve the efficiency of spectrum consumption for wireless multimedia communications. Spectrum sensing, which allows legitimate secondary users (SU) to find vacant bands in the spectrum, plays a vital role in CR networks. When cooperative sensing is used in CR networks, spectrum availability must be taken into account. In many ways, the shared cooperative spectrum sensing (CSS) data among SU. The presence of a malicious user (MU) in the system and sending false sensing data can degrade the performance of cooperative CR. The sharp rise in mobile data tra

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Sun, Zhiguo, Zhenyu Xu, Zengmao Chen, Xiaoyan Ning, and Lili Guo. "Reputation-Based Spectrum Sensing Strategy Selection in Cognitive Radio Ad Hoc Networks." Sensors 18, no. 12 (2018): 4377. http://dx.doi.org/10.3390/s18124377.

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Spectrum sensing plays an essential role in the detection of unused spectrum whole in cognitive radio networks, including cooperative spectrum sensing (CSS) and independent spectrum sensing. In cognitive radio ad hoc networks (CRAHNs), CSS enhances the sensing performance of cognitive nodes by exploring the spectrum partial homogeneity and fully utilizing the knowledge of neighboring nodes, e.g., sensing results and topological information. However, CSS may also open a door for malicious nodes, i.e., spectrum sensing data falsification (SSDF) attackers, which report fake sensing results to det

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Gul, Noor, Su Min Kim, Saeed Ahmed, Muhammad Sajjad Khan, and Junsu Kim. "Differential Evolution Based Machine Learning Scheme for Secure Cooperative Spectrum Sensing System." Electronics 10, no. 14 (2021): 1687. http://dx.doi.org/10.3390/electronics10141687.

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The secondary users (SUs) in cognitive radio networks (CRNs) can obtain reliable spectrum sensing information of the primary user (PU) channel using cooperative spectrum sensing (CSS). Multiple SUs share their sensing observations in the CSS system to tackle fading and shadowing conditions. The presence of malicious users (MUs) may pose threats to the performance of CSS due to the reporting of falsified sensing data to the fusion center (FC). Different categories of MUs, such as always yes, always no, always opposite, and random opposite, are widely investigated by researchers. To this end, th

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Vu-Van, Hiep, and Insoo Koo. "Goodness-of-Fit Based Secure Cooperative Spectrum Sensing for Cognitive Radio Network." Scientific World Journal 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/752507.

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Cognitive radio (CR) is a promising technology for improving usage of frequency band. Cognitive radio users (CUs) are allowed to use the bands without interference in operation of licensed users. Reliable sensing information about status of licensed band is a prerequirement for CR network. Cooperative spectrum sensing (CSS) is able to offer an improved sensing reliability compared to individual sensing. However, the sensing performance of CSS can be destroyed due to the appearance of some malicious users. In this paper, we propose a goodness-of-fit (GOF) based cooperative spectrum sensing sche

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Rudabhai, Keraliya Divyesh, Mehta Rahul Dhirendrabhai, and Loriya Hitesh Thakarshibhai. "Optimization of Quantized Cooperative Sensing Using Multi-Objective JAYA Algorithm." International Research Journal of Multidisciplinary Scope 06, no. 01 (2025): 189–98. https://doi.org/10.47857/irjms.2025.v06i01.02442.

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Cognitive radio (CR) is the new era of wireless technology having objective is to effective utilization of available spectrum. The primary function of cognitive radio is to sense the available free spectrum. The effectiveness of cooperative spectrum sensing (CSS) for searching available free spectrums in network of cognitive radio (CR) has been executed by receiving sensing data from surrounding node which is called CR. The data senses by CR node are transmitted at the central/common node named fusion center using either soft combining techniques or standard hard combining technique. These two

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Gul, Noor, Ijaz Mansoor Qureshi, Sadiq Akbar, Muhammad Kamran, and Imtiaz Rasool. "One-to-Many Relationship Based Kullback Leibler Divergence against Malicious Users in Cooperative Spectrum Sensing." Wireless Communications and Mobile Computing 2018 (September 2, 2018): 1–14. http://dx.doi.org/10.1155/2018/3153915.

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The centralized cooperative spectrum sensing (CSS) allows unlicensed users to share their local sensing observations with the fusion center (FC) for sensing the licensed user spectrum. Although collaboration leads to better sensing, malicious user (MU) participation in CSS results in performance degradation. The proposed technique is based on Kullback Leibler Divergence (KLD) algorithm for mitigating the MUs attack in CSS. The secondary users (SUs) inform FC about the primary user (PU) spectrum availability by sending received energy statistics. Unlike the previous KLD algorithm where the indi

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Tan, Youheng, and Xiaojun Jing. "Efficient Approximations for Optimization of N-Out-of-K Rule for Heterogeneous Cognitive Radio Networks." Applied Sciences 11, no. 7 (2021): 3083. http://dx.doi.org/10.3390/app11073083.

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Spectrum sensing (SS) has attracted much attention due to its important role in the improvement of spectrum efficiency. However, the limited sensing time leads to an insufficient sampling point due to the tradeoff between sensing time and communication time. Although the sensing performance of cooperative spectrum sensing (CSS) is greatly improved by mutual cooperation between cognitive nodes, it is at the expense of computational complexity. In this paper, efficient approximations of the N-out-of-K rule-based CSS scheme under heterogeneous cognitive radio networks are provided to obtain the c

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Xu, Su Qin, Yi Tao Xu, Han Jiang, Xiang Gao, and Kang Luo. "Cooperative Spectrum Sensing with Peer-Assessment for Cognitive Radio Network." Advanced Materials Research 926-930 (May 2014): 2228–32. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.2228.

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Cognitive radio (CR) is a promising technology which has the potential to utilize the scarce spectrum resources with high flexibility and efficiency. It’s well accepted that cooperative spectrum sensing (CSS) with numbers of cognitive users (CUs) located in a wide geographical area can achieve much better sensing performance. However, some CRs may misbehave and provide false sensing information in order to deteriorate the system’s performance. This misbehavior is known as spectrum sensing data falsification (SSDF) attack. In this paper, we propose a secure spectrum sensing scheme using peer-as

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Hu, Hang, Hang Zhang, Hong Yu, and Javad Jafarian. "Throughput Optimization via Cooperative Spectrum Sensing with Novel Frame Structure." Mathematical Problems in Engineering 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/975860.

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In cognitive radio (CR) networks, cooperation can greatly improve the performance of spectrum sensing. In this paper, we propose a novel cooperative spectrum sensing (CSS) frame structure in which CR users conduct spectrum sensing and data transmission concurrently over two different parts of the primary user (PU) spectrum band. Energy detection sensing scheme is used to prove that there exists an optimal sensing bandwidth which yields the highest throughput for the CR network. Thus, we focus on the optimal sensing settings of the proposed sensing scheme in order to maximize the throughput of

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Wang, Shubin, Huiqin Liu, and Kun Liu. "An Improved Clustering Cooperative Spectrum Sensing Algorithm Based on Modified Double-Threshold Energy Detection and Its Optimization in Cognitive Wireless Sensor Networks." International Journal of Distributed Sensor Networks 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/136948.

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Cooperative spectrum sensing (CSS) is a very important technique in cognitive wireless sensor networks, but the channel and multipath affect the sensing performance. For improving the sensing performance, this paper incorporates a modified double-threshold energy detection (MDTED) and the location and channel information to improve the clustering cooperative spectrum sensing (CCSS) algorithm. Within each cluster, the cognitive node with the best channel quality to the fusion center (FC) is chosen as the cluster head (CH), and each node uses the MDTED. The detective information is sent to CH, a

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Lv, Shou Tao, Ze Yang Dai, and Jian Liu. "A Reliable Cooperative Spectrum Sensing Strategy for Cognitive Radios." Applied Mechanics and Materials 347-350 (August 2013): 1773–79. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.1773.

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In cognitive radio networks (CRNs), the secondary users (SUs) need to continuously detect whether the primary users (PUs) occupy the spectrum. In order to improve the spectrum sensing accuracy, a novel reliable cooperative spectrum sensing strategy based on the detection results relayed twice from the secondary relays (SRs) to the secondary source (SS), referred to as CSS-DRT, is proposed in this paper. In this scheme, the spectrum sensing slot is divided into four equal sub-slots. In the first and third sub-slots, the SS and SRs detect the PU by themselves. Then, in the second sub-slot, if th

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Gul, Noor, Ijaz Mansoor Qureshi, Atif Elahi, and Imtiaz Rasool. "Defense against Malicious Users in Cooperative Spectrum Sensing Using Genetic Algorithm." International Journal of Antennas and Propagation 2018 (2018): 1–11. http://dx.doi.org/10.1155/2018/2346317.

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In cognitive radio network (CRN), secondary users (SUs) try to sense and utilize the vacant spectrum of the legitimate primary user (PU) in an efficient manner. The process of cooperation among SUs makes the sensing more authentic with minimum disturbance to the PU in achieving maximum utilization of the vacant spectrum. One problem in cooperative spectrum sensing (CSS) is the occurrence of malicious users (MUs) sending false data to the fusion center (FC). In this paper, the FC takes a global decision based on the hard binary decisions received from all SUs. Genetic algorithm (GA) using one-t

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Al-Saggaf, Ubaid M., Jawwad Ahmad, Mohammed A. Alrefaei, and Muhammad Moinuddin. "Optimized Statistical Beamforming for Cooperative Spectrum Sensing in Cognitive Radio Networks." Mathematics 11, no. 16 (2023): 3533. http://dx.doi.org/10.3390/math11163533.

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In cognitive radio (CR), cooperative spectrum sensing (CSS) employs a fusion of multiple decisions from various secondary user (SU) nodes at a central fusion center (FC) to detect spectral holes not utilized by the primary user (PU). The energy detector (ED) is a well-established technique of spectrum sensing (SS). However, a major challenge in designing an energy detector-based SS is the requirement of correct knowledge for the distribution of decision statistics. Usually, the Gaussian assumption is employed for the received statistics, which is not true in real practice, particularly with a

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Gul, Noor, Muhammad Sajjad Khan, Su Min Kim, Junsu Kim, Atif Elahi, and Zafar Khalil. "Boosted Trees Algorithm as Reliable Spectrum Sensing Scheme in the Presence of Malicious Users." Electronics 9, no. 6 (2020): 1038. http://dx.doi.org/10.3390/electronics9061038.

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Cooperative spectrum sensing (CSS) has the ability to accurately identify the activities of the primary users (PUs). As the secondary users’ (SUs) sensing performance is disturbed in the fading and shadowing environment, therefore the CSS is a suitable choice to achieve better sensing results compared to individual sensing. One of the problems in the CSS occurs due to the participation of malicious users (MUs) that report false sensing data to the fusion center (FC) to misguide the FC’s decision about the PUs’ activity. Out of the different categories of MUs, Always Yes (AY), Always No (AN), A

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Wu, Jun, Zhaoyang Qiu, Mingyuan Dai, Jianrong Bao, Xiaorong Xu, and Weiwei Cao. "Distributed Sequential Detection for Cooperative Spectrum Sensing in Cognitive Internet of Things." Sensors 24, no. 2 (2024): 688. http://dx.doi.org/10.3390/s24020688.

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The rapid development of wireless communication technology has led to an increasing number of internet of thing (IoT) devices, and the demand for spectrum for these devices and their related applications is also increasing. However, spectrum scarcity has become an increasingly serious problem. Therefore, we introduce a collaborative spectrum sensing (CSS) framework in this paper to identify available spectrum resources so that IoT devices can access them and, meanwhile, avoid causing harmful interference to the normal communication of the primary user (PU). However, in the process of sensing t

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Yang, Kai, Shengbo Hu, Xin Zhang, Tingting Yan, and Manqin Zhu. "CSL-SFNet for Cooperative Spectrum Sensing in Cognitive Satellite Network with GEO and LEO Satellites." IET Signal Processing 2024 (April 29, 2024): 1–12. http://dx.doi.org/10.1049/2024/5897908.

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In a cognitive satellite network (CSN) with GEO and LEO satellites, there is a large propagation losses between the sensing satellite and the ground station. The results of spectrum sensing from a single satellite may be inaccurate, which will create serious interference in the primary satellite system. Cooperative spectrum sensing (CSS) has become the key technology for solving the above problems in recent years. However, most of the current CSS techniques are model-driven. They are difficult to model and implement in CSNs since their detection performance is strongly dependent on an assumed

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Vaduganathan, Lakshminarayanan, Shubhangi Neware, Przemysław Falkowski-Gilski, and Parameshachari Bidare Divakarachari. "Spectrum Sensing Based on Hybrid Spectrum Handoff in Cognitive Radio Networks." Entropy 25, no. 9 (2023): 1285. http://dx.doi.org/10.3390/e25091285.

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The rapid advancement of wireless communication combined with insufficient spectrum exploitation opens the door for the expansion of novel wireless services. Cognitive radio network (CRN) technology makes it possible to periodically access the open spectrum bands, which in turn improves the effectiveness of CRNs. Spectrum sensing (SS), which allows unauthorized users to locate open spectrum bands, plays a fundamental part in CRNs. A precise approximation of the power spectrum is essential to accomplish this. On the assumption that each SU’s parameter vector contains some globally and partially

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Liu, Xiaoying, and Kechen Zheng. "Trade-Offs among Sensing, Reporting, and Transmission in Cooperative CRNs." Sensors 22, no. 13 (2022): 4753. http://dx.doi.org/10.3390/s22134753.

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Cooperative spectrum sensing (CSS) has been verified as an effective approach to improve the sensing performances of cognitive radio networks (CRNs). Compared with existing works that commonly consider fusion with fixed inputs and neglect the duration of the reporting period in the design, we novelly investigate a fundamental trade-off among three periods of CSS: sensing, reporting, and transmission periods, and evaluate the impact of the fusion rule with a varying number of local sensing results. To be specific, the sensing time could be traded for additional mini-slots to report more local s

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Lu, Lingyun, Xiang Li, Guizhu Wang, and Wei Ni. "Multiband Cooperative Spectrum Sensing Meets Vehicular Network: Relying on CNN-LSTM Approach." Wireless Communications and Mobile Computing 2023 (June 16, 2023): 1–8. http://dx.doi.org/10.1155/2023/4352786.

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A vehicular network is expected to empower all aspects of the intelligent transportation system (ITS) and aim at improving road safety and traffic efficiency. In view of the fact that spectrum scarcity becomes more severe owing to the increasing number of connected vehicles, implying spectrum sensing technology in vehicular network, i.e., cognitive vehicular network, has emerged as a promising solution to provide opportunistic usage of licensed spectrum. However, some unique features of vehicular networks, such as high movement and dynamic topology, take on high challenges for spectrum sensing

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Yavanika, N., S. Vasikaran, and J. Balavishnu. "Optimizing Spectrum Sensing using Average Slope Detection and Machine Learning Techniques." International Journal of Microsystems and IoT 3, no. 1 (2025): 1473–79. https://doi.org/10.5281/zenodo.15463178.

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The cognitive radio network represents a pivotal advancement for 5G applications, countering the limitations posed by spectrum scarcity. Spectrum sensing is vital for identifying vacant spectrum bands in a network framework that comprises of Primary User (PU) and Secondary Users (SU’s). The traditional spectrum sensing scheme like Energy detection is highly sensitive to uncertainties in noise with limited sensing accuracy. To overcome this limitation a novel method, Average Slope Detection (ASD) with Cooperative Spectrum Sensing is proposed. The Cooperative Spectrum Sensing network is si

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Zhao, Feng, Shaoping Li, and Jingyu Feng. "Securing Cooperative Spectrum Sensing against DC-SSDF Attack Using Trust Fluctuation Clustering Analysis in Cognitive Radio Networks." Wireless Communications and Mobile Computing 2019 (March 3, 2019): 1–11. http://dx.doi.org/10.1155/2019/3174304.

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Cooperative spectrum sensing (CSS) has been recognized as a forceful approach to promote the utilization of spectrum bands. Nevertheless, all secondary users (SU) are assumed as honest in CSS, thus giving opportunities for attackers to launch the spectrum sensing data falsification (SSDF) attack. To defend against such attack, many efforts have been made to trust mechanism. In this paper, we argue that securing CSS with only trust mechanism is not enough and report the description of dynamic-collusive SSDF attack (DC-SSDF attack). To escape the detection of trust mechanism, DC-SSDF attackers c

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Men, Shaoyang, Pascal Chargé, and Sébastien Pillement. "A Robust and Energy Efficient Cooperative Spectrum Sensing Scheme in Cognitive Wireless Sensor Networks." Network Protocols and Algorithms 7, no. 3 (2015): 140. http://dx.doi.org/10.5296/npa.v7i3.8254.

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Cooperative spectrum sensing (CSS) is able to effectively solve the hidden terminal, depth attenuation, multipath shadows and other issues which are not addressed by the single-user sensing. Therefore, it has attracted a large amount of interest and several CSS algorithms have been proposed. However, they are not specifically tailored for cognitive wireless sensor networks (CWSNs) where transmission reliability, power management and interference avoidance are critical issues. In this paper, we propose a robust and energy efficient CSS scheme in CWSNs. Firstly, taking into account the limited e

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Jerry, Raymond Adekogba Opeyemi Olajumoke Maxwell Francisc Aliyu Danjuma Usman. "A Review of Spectrum Sensing Times in Cognitive Radio Networks." Advances in Engineering Design Technology 5, no. 1 (2023): 29–42. https://doi.org/10.5281/zenodo.7781932.

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<em>The introduction of Cognitive Radio (CR) to ensure the efficient utilization of radio spectrum resources, where the opportunistic unlicensed user called the Secondary User (SU) jumped into a temporary unused spectrum owned by the licensed user called the Primary User (PU) for data transmission without causing interference. The CR is the key enabling technology that enables next generation communication system also known as Dynamic Spectrum Access (DSA) networks to efficiently utilize Radio Frequency (RF) spectrum effectively. The CR has opened more research areas among which is the Spectru

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Xie, Gang, Xincheng Zhou, and Jinchun Gao. "Adaptive Trust Threshold Model Based on Reinforcement Learning in Cooperative Spectrum Sensing." Sensors 23, no. 10 (2023): 4751. http://dx.doi.org/10.3390/s23104751.

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In cognitive radio systems, cooperative spectrum sensing (CSS) can effectively improve the sensing performance of the system. At the same time, it also provides opportunities for malicious users (MUs) to launch spectrum-sensing data falsification (SSDF) attacks. This paper proposes an adaptive trust threshold model based on a reinforcement learning (ATTR) algorithm for ordinary SSDF attacks and intelligent SSDF attacks. By learning the attack strategies of different malicious users, different trust thresholds are set for honest and malicious users collaborating within a network. The simulation

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Peng, Guangqian, and Wei Wu. "Fusion Schemes Based on IRS-Enhanced Cooperative Spectrum Sensing for Cognitive Radio Networks." Electronics 11, no. 16 (2022): 2533. http://dx.doi.org/10.3390/electronics11162533.

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The detection performance of cooperative spectrum sensing (CSS) is poor when there are obstacles blocking. Therefore, fusion schemes based on intelligent reflecting surface (IRS)-enhanced CSS are investigated. Existing fusion schemes can be divided into the soft combination and the hard combination. In the soft combination, each secondary user (SU) uploads the decision statistic to a fusion center (FC). Comparatively, during the hard combination, each SU reports the local 0/1 decision result to FC instead of decision statistic. In this paper, the equal gain combination (EGC) and the selection

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Wu, Jun, Tianle Liu, and Rui Zhao. "Beta Distribution Function for Cooperative Spectrum Sensing against Byzantine Attack in Cognitive Wireless Sensor Networks." Electronics 13, no. 17 (2024): 3386. http://dx.doi.org/10.3390/electronics13173386.

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In order to explore more spectrum resources to support sensors and their related applications, cognitive wireless sensor networks (CWSNs) have emerged to identify available channels being underutilized by the primary user (PU). To improve the detection accuracy of the PU signal, cooperative spectrum sensing (CSS) among sensor paradigms is proposed to make a global decision about the PU status for CWSNs. However, CSS is susceptible to Byzantine attacks from malicious sensor nodes due to its open nature, resulting in wastage of spectrum resources or causing harmful interference to PUs. To suppre

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Bani, Kavita, and Vaishali Kulkarni. "Hybrid Spectrum Sensing Using MD and ED for Cognitive Radio Networks." Journal of Sensor and Actuator Networks 11, no. 3 (2022): 36. http://dx.doi.org/10.3390/jsan11030036.

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Day by day, the demand for wireless systems is increasing while the available spectrum resources are not sufficient. To fulfil the demand for wireless systems, the spectrum hole (spectrum vacant) should be found and utilised very effectively. Cognitive radio (CR) is a device which intelligently senses the spectrum through various spectrum-sensing detectors. Based on the complexity and licensed user’s information present with CR, the appropriate detector should be utilised for spectrum sensing. In this paper, a hybrid detector (HD) is proposed to determine the spectrum hole from the available s

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Ahmed, Arshed, Muhammad Sajjad Khan, Noor Gul, Irfan Uddin, Su Min Kim, and Junsu Kim. "A Comparative Analysis of Different Outlier Detection Techniques in Cognitive Radio Networks with Malicious Users." Wireless Communications and Mobile Computing 2020 (December 9, 2020): 1–18. http://dx.doi.org/10.1155/2020/8832191.

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In a cognitive radio (CR), opportunistic secondary users (SUs) periodically sense the primary user’s (PU’s) existence in the network. Spectrum sensing of a single SU is not precise due to wireless channels and hidden terminal issues. One promising solution is cooperative spectrum sensing (CSS) that allows multiple SUs’ cooperation to sense the PU’s activity. In CSS, the misdetection of the PU signal by the SU causes system inefficiency that increases the interference to the system. This paper introduces a new category of a malicious user (MU), i.e., a lazy malicious user (LMU) with two operati

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Jiang, Kejian, Chi Ma, Ruiquan Lin, Jun Wang, Weibing Jiang, and Haifeng Hou. "Free-Rider Games for Cooperative Spectrum Sensing and Access in CIoT Networks." Sensors 23, no. 13 (2023): 5828. http://dx.doi.org/10.3390/s23135828.

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With the rapid development of technologies such as wireless communications and the Internet of Things (IoT), the proliferation of IoT devices will intensify the competition for spectrum resources. The introduction of cognitive radio technology in IoT can minimize the shortage of spectrum resources. However, the open environment of cognitive IoT may involve free-riding problems. Due to the selfishness of the participants, there are usually a large number of free-riders in the system who opportunistically gain more rewards by stealing the spectrum sensing results from other participants and acce

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Chen, Siji, Bin Shen, Xin Wang, and Sang-Jo Yoo. "A Strong Machine Learning Classifier and Decision Stumps Based Hybrid AdaBoost Classification Algorithm for Cognitive Radios." Sensors 19, no. 23 (2019): 5077. http://dx.doi.org/10.3390/s19235077.

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Machine learning (ML) based classification methods have been viewed as one kind of alternative solution for cooperative spectrum sensing (CSS) in recent years. In this paper, ML techniques based CSS algorithms are investigated for cognitive radio networks (CRN). Specifically, a strong machine learning classifier (MLC) and decision stumps (DS) based adaptive boosting (AdaBoost) classification mechanism is proposed for pattern classification of the primary user’s behavior in the network. The conventional AdaBoost algorithm only combines multiple sub-classifiers and produces a strong weight based

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Li, Jingxian, and Bin-Jie Hu. "Quantized Cooperative Spectrum Sensing in Bandwidth-Constrained Cognitive V2X Based on Deep Learning." Electronics 10, no. 11 (2021): 1315. http://dx.doi.org/10.3390/electronics10111315.

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The output of the network in a deep learning (DL) based single-user signal detector, which is a normalized 2 × 1 class score vector, needs to be transmitted to the fusion center (FC) by occupying a large amount of the communication channel (CCH) bandwidth in the cooperative spectrum sensing (CSS). Obviously, in cognitive radio for vehicle to everything (CR-V2X), it is particularly important to propose a method that makes full use of the bandwidth-constrained CCH to obtain the optimal detection performance. In this paper, we firstly propose a novel single-user spectrum sensing method based on m

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Devaraj, Stalin Allwin, Kambatty Bojan Gurumoorthy, Pradeep Kumar, Wilson Stalin Jacob, Prince Jenifer Darling Rosita, and Tanweer Ali. "Cluster-ID-Based Throughput Improvement in Cognitive Radio Networks for 5G and Beyond-5G IOT Applications." Micromachines 13, no. 9 (2022): 1414. http://dx.doi.org/10.3390/mi13091414.

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Cognitive radio (CR), which is a common form of wireless communication, consists of a transceiver that is intelligently capable of detecting which communication channels are available to use and which are not. After this detection process, the transceiver avoids the occupied channels while simultaneously moving into the empty ones. Hence, spectrum shortage and underutilization are key problems that the CR can be proposed to address. In order to obtain a good idea of the spectrum usage in the area where the CRs are located, cooperative spectrum sensing (CSS) can be used. Hence, the primary obje

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K, Venkata Vara Prasad, and Trinatha Rao P. "LEARNING BASED COOPERATIVE SPECTRUM SENSING FOR PRIMARY USER DETECTION IN COGNITIVE RADIO NETWORKS." ICTACT Journal on Communication Technology 11, no. 3 (2020): 2243–49. https://doi.org/10.21917/ijct.2020.0332.

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In Cognitive Radio Networks (CRN) spectrum sensing plays an important role in achieving spectrum utilization fast and accurately. Due to interference, power levels and hidden terminal problem, it becomes challenging to detect the presence of primary users accurately with better spectrum efficiency. Thus detection of primary users has become an important research problem in cognitive radio network. In this paper proposed a learning methods to detect the presence of primary user with high accuracy. The proposed classifiers has been trained using the extracted features to detect PU’s signal in lo

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Venkatapathi, Pella, Habibulla Khan, S. Srinivasa Rao, and Govardhani Immadi. "Cooperative Spectrum Sensing Performance Assessment using Machine Learning in Cognitive Radio Sensor Networks." Engineering, Technology & Applied Science Research 14, no. 1 (2024): 12875–79. http://dx.doi.org/10.48084/etasr.6639.

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The Cognitive Radio (CR) is an imminent technology, intended to make more effective use of the available spectrum by giving access to licensed frequency bands by unlicensed Secondary Users (SUs) without affecting Primary licensed Users (PUs). Depending on the region where the energy is being observed, each CR communicates local decisions or the seen energy to the Fusion Center (FC). This study presents the many plots that discuss an enhanced double threshold through the Cooperative Spectrum Sensing (CSS) approach. The FC then combines local decisions with the measured energy values to reach a

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Yao, Changhua, and Qihui Wu. "A Hybrid Combination Scheme for Cooperative Spectrum Sensing in Cognitive Radio Networks." Mathematical Problems in Engineering 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/106106.

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We propose a novel hybrid combination scheme in cooperative spectrum sensing (CSS), which utilizes the diversity of reporting channels to achieve better throughput performance. Secondary users (SUs) with good reporting channel quality transmit quantized local observation statistics to fusion center (FC), while others report their local decisions. FC makes the final decision by carrying out hybrid combination. We derive the closed-form expressions of throughput and detection performance as a function of the number of SUs which report local observation statistics. The simulation and numerical re

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dos Santos Costa, Lucas, Fátima Sayury Queralt Queda Alves, and Rausley Adriano Amaral de Souza. "Multiantenna-Cognitive-Radio-Based Blind Spectrum Sensing under Correlated Signals and Unequal Signal and Noise Powers." Electronics 11, no. 11 (2022): 1719. http://dx.doi.org/10.3390/electronics11111719.

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Adopting cognitive radios (CRs) having multiple antennas in blind non-cooperative and cooperative spectrum sensing (CSS) under fading channels has gained attention due to higher detection performances provided by the spatial diversity gain of multi-sensors in different geographical locations and lower complexity, respectively. However, most studies do not consider sensing scenarios of more practical significance: for example, sometimes adopting only uncalibrated antenna arrays and sometimes only correlated signals at antenna arrays of CRs, but almost always, none of these impairments. Therefor

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Koyuncu, Hakan, Ashish Bagwari, and Geetam Singh Tomar. "Simulation of a Smart Sensor Detection Scheme for Wireless Communication Based on Modeling." Electronics 9, no. 9 (2020): 1506. http://dx.doi.org/10.3390/electronics9091506.

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The principle of sensing and sending information applies to all kinds of communications in different media like air, water, etc. During data transmission through sensors, the most important issue is sensing failure problems. In communication systems, sensing failure problems generally occur and affect sensor system performance. In this study, sensing failure issues are discussed, and a smart sensor is introduced that detects the communication signals. The characteristics of these sensors are identified with signal-to-noise ratio (SNR) readings. The proposed sensor system has high performance a

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VARMA, ASHWINI KUMAR, BITTU KUMAR, AKELLA RAMAKRISHNA, and DEBJANI MITRA. "MULTI-HOP RELAY SELECTION FOR COOPERATIVE SENSING IN COGNITIVE RADIO NETWORKS." REVUE ROUMAINE DES SCIENCES TECHNIQUES — SÉRIE ÉLECTROTECHNIQUE ET ÉNERGÉTIQUE 69, no. 2 (2024): 237–42. http://dx.doi.org/10.59277/rrst-ee.2024.2.20.

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Spectrum sensing is one of the essential blocks of the cognitive radio (CR) system. Cooperative spectrum sensing (CSS) enhances sensing performance by exchanging information among secondary users (SUs). The paper addresses a situation where some SUs cannot communicate their local information with the fusion center (FC) due to real-time circumstances, i.e., shadowing, large distances, increased signal interference, etc. The issue can be resolved by introducing relay nodes to assist such SUs in transmitting local information to the corresponding destination (FC), making relay selection an essent

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Zhu, Cao, and Mu. "A Further Exploration of Multi-Slot Based Spectrum Sensing." Sensors 19, no. 16 (2019): 3497. http://dx.doi.org/10.3390/s19163497.

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Spectrum sensing (SS) exhibits its advantages in the era of Internet of Things (IoT) due to limited spectrum resource and a lower utilization rate of authorized spectrum. In consequence, the performance improvement of SS seems a matter of great significance for the development of wireless communication and IoT. Motivated by this, this paper is devoted to multi-slot based SS in specialty and several important conclusions are drawn. Firstly, SS with one slot outperforms those with multiple slots if decision fusion rule is considered for multi-slot based SS. Secondly, multi-slot based SS is condu

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Tephillah, S., and J. Martin Leo Manickam. "An SETM Algorithm for Combating SSDF Attack in Cognitive Radio Networks." Wireless Communications and Mobile Computing 2020 (July 21, 2020): 1–9. http://dx.doi.org/10.1155/2020/9047809.

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Security is a pending challenge in cooperative spectrum sensing (CSS) as it employs a common channel and a controller. Spectrum sensing data falsification (SSDF) attacks are challenging as different types of attackers use them. To address this issue, the sifting and evaluation trust management algorithm (SETM) is proposed. The necessity of computing the trust for all the secondary users (SUs) is eliminated based on the use of the first phase of the algorithm. The second phase is executed to differentiate the random attacker and the genuine SUs. This reduces the computation and overhead costs.

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