Relevant bibliographies by topics / Cooperative Spectrum Sensing (CSS)

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Cooperative Spectrum Sensing (CSS)'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Cooperative Spectrum Sensing (CSS)"

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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>&nbsp;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.&nbsp;<strong>Methodology:</strong>&nbsp;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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Dissertations / Theses on the topic "Cooperative Spectrum Sensing (CSS)"

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Simpson, Oluyomi. "Optimal cooperative spectrum sensing for cognitive radio." Thesis, University of Hertfordshire, 2016. http://hdl.handle.net/2299/17246.

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The rapid increasing interest in wireless communication has led to the continuous development of wireless devices and technologies. The modern convergence and interoperability of wireless technologies has further increased the amount of services that can be provided, leading to the substantial demand for access to the radio frequency spectrum in an efficient manner. Cognitive radio (CR) an innovative concept of reusing licensed spectrum in an opportunistic manner promises to overcome the evident spectrum underutilization caused by the inflexible spectrum allocation. Spectrum sensing in an unsw
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Balakrishnan, Gautam. "Cognitive radio cooperative spectrum sensing." Thesis, California State University, Long Beach, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10252432.

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<p> The effectiveness of a cognitive radio (CR) system depends mainly on involved spectrum sensing techniques. The main aim of CR is for effective utilization of the spectrum opportunistically by sharing it with secondary users (SUs), when the primary user (PU) is absent. In this project, cooperative spectrum sensing using weights based on the distance measures from the PU and Multitaper Method (MTM) method is briefly explained. The results show that MTM method provides more accurate threshold value compared to other methods for low signal to noise ratios (SNRs), hence improving the spectrum s
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Noel, Adam Josiah Gerald. "Convex sensing-reporting optimization for cooperative spectrum sensing." Thesis, University of British Columbia, 2011. http://hdl.handle.net/2429/36838.

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In this thesis, we consider the cooperative spectrum sensing problem in cognitive radio with energy detection. Secondary users with non-identical, independent sensing channels make 1-bit sensing decisions and report their decisions to the secondary base station over orthogonal noisy fading channels. The base station has knowledge of the reporting channel coefficients and acts as a fusion center by combining the decisions with an M-out-of-K rule. We allow the secondary users to trade sensing time slots for additional reporting time slots to increase the signal-to-noise ratios of the reporting c
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Prawatmuang, Warit. "Cooperative spectrum sensing for cognitive radio." Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/cooperative-spectrum-sensing-for-cognitive-radio(db1dd626-841e-4b05-b5af-fa27e59c63bb).html.

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Cognitive Radio (CR) aims to access the wireless spectrum in an opportunistic manner while the licensed user is not using it. To accurately determine the licensed user's existence, spectrum sensing procedure is vital to CR system. Energy detection-based spectrum sensing techniques is favourable due to its simplicity and low complexity. In addition, to improve the detection performance, cooperative spectrum sensing technique exploits multi-user diversity and mitigates detection uncertainty. In this thesis, we investigate several energy detection based cooperative spectrum sensing techniques.Fir
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Kaligineedi, Praveen. "Cooperative spectrum sensing for cognitive radio networks." Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/30261.

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Radio spectrum is a very scarce and important resource for wireless communication systems. However, a recent study conducted by Federal Communications Commission (FCC) found that most of the currently allocated radio spectrum is not efficiently utilized by the licensed primary users. Granting opportunistic access of the spectrum to unlicensed secondary users has been suggested as a possible way to improve the utilization of the radio spectrum. Cognitive Radio (CR) is an emerging technology that would allow an unlicensed (cognitive) radio to sense and efficiently use any available spectrum at a
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Sharkasi, Youssif F. "Cooperative spectrum sensing : performance analysis and algorithms." Thesis, University of Leeds, 2014. http://etheses.whiterose.ac.uk/8369/.

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The employment of cognitive (intelligent) radios presents an opportunity to efficiently use the scarce spectrum with the condition that it causes a minimal disturbance to the primary user. So the cognitive or secondary users use spectrum sensing to detect the presence of primary user. In this thesis, different aspects related to spectrum sensing and cognitive radio performance are theoretically studied for the discussion and in most cases, closedform expressions are derived. Simulations results are also provided to verify the derivations. Firstly, robust spectrum sensing techniques are propose
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Teguig, Djamel. "Cooperative Spectrum Sensing Algorithms For Cognitive Radio Networks." Doctoral thesis, Universite Libre de Bruxelles, 2015. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/219942.

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The work presented in this thesis concerns one of the key enabling techniques related to cognitive radio functionalities which is spectrum sensing as well as cooperative spectrum sensing. As cooperative spectrum sensing (CSS) approaches are commonly used for combating fading and improving detection performance, their performances using different combining rules have been analyzed. Due to the low implementation complexity, Goodness of Fit based spectrum sensing has been studied for cognitive radio applications. Motivated by its nice features of local sensing, a distributed consensus spectrum se
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jowkar, ghazaleh. "Cooperative Wideband Spectrum Sensing Based on Joint Sparsity." VCU Scholars Compass, 2017. http://scholarscompass.vcu.edu/etd/5055.

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COOPERATIVE WIDEBAND SPECTRUM SENSING BASED ON JOINT SPARSITY By Ghazaleh Jowkar, Master of Science A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science at Virginia Commonwealth University Virginia Commonwealth University 2017 Major Director: Dr. Ruixin Niu, Associate Professor of Department of Electrical and Computer Engineering In this thesis, the problem of wideband spectrum sensing in cognitive radio (CR) networks using sub-Nyquist sampling and sparse signal processing techniques is investigated. To mitigate multi-path fading, it is assumed that
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Althunibat, Saud. "Towards Energy Efficient Cooperative Spectrum Sensing in Cognitive Radio Networks." Doctoral thesis, Università degli studi di Trento, 2014. https://hdl.handle.net/11572/367952.

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Cognitive radio has been proposed as a promising technology to resolve the spectrum scarcity problem by dynamically exploiting underutilized spectrum bands. Cognitive radio technology allows unlicensed users, also called cognitive users (CUs), to exploit the spectrum vacancies at any time with no or limited extra interference at the licensed users. Usually, cognitive radios create networks in order to better identify spectrum vacancies, avoid resultant interference, and consequently, magnify their revenues. One of the main challenges in cognitive radio networks is the high energy consumption,
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Althunibat, Saud. "Towards Energy Efficient Cooperative Spectrum Sensing in Cognitive Radio Networks." Doctoral thesis, University of Trento, 2014. http://eprints-phd.biblio.unitn.it/1335/1/PhD_Dissertaion_Althunibat_Saud.pdf.

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Cognitive radio has been proposed as a promising technology to resolve the spectrum scarcity problem by dynamically exploiting underutilized spectrum bands. Cognitive radio technology allows unlicensed users, also called cognitive users (CUs), to exploit the spectrum vacancies at any time with no or limited extra interference at the licensed users. Usually, cognitive radios create networks in order to better identify spectrum vacancies, avoid resultant interference, and consequently, magnify their revenues. One of the main challenges in cognitive radio networks is the high energy consumption,
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Books on the topic "Cooperative Spectrum Sensing (CSS)"

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Fernando, Xavier, Ajmery Sultana, Sattar Hussain, and Lian Zhao. Cooperative Spectrum Sensing and Resource Allocation Strategies in Cognitive Radio Networks. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-73957-1.

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Zhao, Lian, Xavier Fernando, Ajmery Sultana, and Sattar Hussain. Cooperative Spectrum Sensing and Resource Allocation Strategies in Cognitive Radio Networks. Springer, 2018.

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Benedetto, Maria-Gabriella Di, and Faouzi Bader. Cognitive Communication and Cooperative HetNet Coexistence: Selected Advances on Spectrum Sensing, Learning, and Security Approaches. Springer, 2014.

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Benedetto, Maria-Gabriella Di, and Faouzi Bader. Cognitive Communication and Cooperative Hetnet Coexistence: Selected Advances on Spectrum Sensing, Learning, and Security Approaches. Springer International Publishing AG, 2016.

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Benedetto, Maria-Gabriella Di, and Faouzi Bader. Cognitive Communication and Cooperative HetNet Coexistence: Selected Advances on Spectrum Sensing, Learning, and Security Approaches. Springer London, Limited, 2014.

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Book chapters on the topic "Cooperative Spectrum Sensing (CSS)"

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Dhope, Tanuja Shendkar. "Cooperative Spectrum Sensing." In Cognitive Radio Networks Optimization with Spectrum Sensing Algorithms. River Publishers, 2022. http://dx.doi.org/10.1201/9781003337607-3.

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Yilmaz, H. Birkan, Salim Eryigit, and Tuna Tugcu. "Cooperative Spectrum Sensing." In Cognitive Radio and Networking for Heterogeneous Wireless Networks. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-01718-1_3.

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Captain, Kamal M., and Manjunath V. Joshi. "Cooperative Wideband Spectrum Sensing." In Spectrum Sensing for Cognitive Radio. CRC Press, 2021. http://dx.doi.org/10.1201/9781003088554-7.

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Fernando, Xavier, Ajmery Sultana, Sattar Hussain, and Lian Zhao. "Relay-Based Cooperative Spectrum Sensing." In SpringerBriefs in Electrical and Computer Engineering. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73957-1_2.

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Caso, Giuseppe, Luca De Nardis, Ragnar Thobaben, and Maria-Gabriella Di Benedetto. "Cooperative Sensing of Spectrum Opportunities." In Opportunistic Spectrum Sharing and White Space Access. John Wiley & Sons, Inc, 2015. http://dx.doi.org/10.1002/9781119057246.ch7.

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Zhou, X., G. Y. Li, D. Li, D. Wang, and A. C. K. Soong. "Bandwidth-Efficient Cooperative Spectrum Sensing." In Lecture Notes in Electrical Engineering. Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-1827-2_3.

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TAN, Ruilian. "Research on Adaptive Cooperative Spectrum Sensing." In Advances on P2P, Parallel, Grid, Cloud and Internet Computing. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49109-7_46.

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Wang, Tianyu, Lingyang Song, Walid Saad, and Zhu Han. "Cooperative Spectrum Sensing in Cognitive Radio." In SpringerBriefs in Electrical and Computer Engineering. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-25700-6_3.

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Gao, Yu, Xin-Lin Huang, Si-Yue Sun, Xiaowei Tang, and Yuan Xu. "Research on Cooperative Spectrum Sensing Algorithm." In Machine Learning and Intelligent Communications. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52730-7_35.

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Ning, Wenli, Xiaoyan Huang, Fan Wu, Supeng Leng, and Lixiang Ma. "Reinforcement Learning-Based Cooperative Spectrum Sensing." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14657-3_16.

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Conference papers on the topic "Cooperative Spectrum Sensing (CSS)"

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Serghini, Omar, Salvatore Serrano, Hayat Semlali, and Asmaa Maali. "Robust DNN-Enabled Cooperative Spectrum Sensing." In 2024 International Conference on Software, Telecommunications and Computer Networks (SoftCOM). IEEE, 2024. http://dx.doi.org/10.23919/softcom62040.2024.10721894.

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Ji, Xi, Quan Liu, Wenjun Xu, and Duzhong Zhang. "Complexity Optimization for Cooperative Sensing Using Coalition Games." In ASME 2014 International Manufacturing Science and Engineering Conference collocated with the JSME 2014 International Conference on Materials and Processing and the 42nd North American Manufacturing Research Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/msec2014-4078.

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Cognitive radio is a far effective method to solve the problem of limited spectrum resources in the wireless communication in cloud manufacturing, involved in kinds of networks. Cooperative spectrum sensing, as a research hotspot in cognitive radio, can improve the sensing quality in cognitive radio networks, but it will also bring in extra cost when forming coalitions and conduct cooperative spectrum sensing. Although CSS based on coalition formation games can significantly conquer this problem by improving the sensing quality and at the same time reducing extra cost, it is much too complex w
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C. Dike, Blessing, and Cajetan M. Akujuobi. "A Study of Cooperative and Non-Cooperative Wideband Spectrum Sensing Radio Networks in the Cognitive Radio 5G Era." In 10th International Conference on Computer Science, Engineering and Information Technology. Academy & Industry Research Collaboration Center, 2024. http://dx.doi.org/10.5121/csit.2024.141903.

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The advent of 5G technologies has ushered in unprecedented demands for efficient spectrum utilization to accommodate a surge in data traffic and diverse communication services. In this context, accurate and reliable spectrum sensing is crucial. We investigated wideband spectrum sensing strategies by comparing non-cooperative cognitive radio (CR) approaches with cooperative methods across multiple sub-bands. Our research led to the development of a sophisticated cooperative wideband spectrum sensing framework that incorporates a K-out-of-N fusion rule at the fusion center to make optimal decisi
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Fangrong Peng, Hao Chen, and Biao Chen. "On energy detection for cooperative spectrum sensing." In 2012 46th Annual Conference on Information Sciences and Systems (CISS). IEEE, 2012. http://dx.doi.org/10.1109/ciss.2012.6310855.

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Sheng Wang and Nazanin Rahnavard. "Eigenvalue-based cooperative spectrum sensing with finite samples/sensors." In 2012 46th Annual Conference on Information Sciences and Systems (CISS). IEEE, 2012. http://dx.doi.org/10.1109/ciss.2012.6310858.

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Seunghyun Choi and Kang G. Shin. "Secure cooperative spectrum sensing in cognitive radio networks using interference signatures." In 2013 IEEE Conference on Communications and Network Security (CNS). IEEE, 2013. http://dx.doi.org/10.1109/cns.2013.6682688.

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Xiong, Gang, and Shalinee Kishore. "Cooperative spectrum sensing in cognitive radio networks under Gaussian fusion channels." In 2009 43rd Annual Conference on Information Sciences and Systems (CISS). IEEE, 2009. http://dx.doi.org/10.1109/ciss.2009.5054803.

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Xiong, Gang, Shalinee Kishore, and Aylin Yener. "On performance evaluation of cooperative spectrum sensing in cognitive radio networks." In 2010 44th Annual Conference on Information Sciences and Systems (CISS). IEEE, 2010. http://dx.doi.org/10.1109/ciss.2010.5464933.

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Reisi, Nima, Vahid Jamali, and Mahmoud Ahmadian. "Linear decision fusion based cooperative spectrum sensing in cognitive radio networks." In 2012 16th CSI International Symposium on Artificial Intelligence and Signal Processing (AISP). IEEE, 2012. http://dx.doi.org/10.1109/aisp.2012.6313746.

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Zhendong, Wang, Wang Huiqiang, Feng Guangsheng, Lv Hongwu, and Zhu Qiang. "A Novel Cooperative Spectrum Sensing Approach Against Malicious Users in Cognitive Radio Networks." In 2013 International Conference on Computer Sciences and Applications (CSA). IEEE, 2013. http://dx.doi.org/10.1109/csa.2013.44.

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Reports on the topic "Cooperative Spectrum Sensing (CSS)"

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Zhou, Daniel. Wideband Cooperative Spectrum Sensing and Signal Detection (Briefing Slides). Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada587302.

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