Advances on Spectrum Sensing for Cognitive Radio Networks: Theory and Applications

Ali, Abdelmohsen; Hamouda, Walaa

doi:10.1109/comst.2016.2631080

Cited by 506 publications

(257 citation statements)

References 210 publications

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“…Several survey papers exist in the literature in the context of dynamic spectrum sharing and spectral coexistence covering a wide range of areas such as spectrum occupancy modeling and measurements [29,30], interweave DSS [31,32,34], underlay DSS [35][36][37], overlay DSS [38], MAC protocols for DSS [39], spectrum decision [43], spectrum assignment [44], security for DSS [40], learning for DSS [41,42], DSS under practical imperfections [13], licensed spectrum sharing [61][62][63] IoT, M2M and D2D [64][65][66][67] techniques [45], and the coexistence of LTE and WiFi [46]. Furthermore, the contribution in [37] provided a comprehensive review of radio resource allocation techniques for efficient spectrum sharing based on different design techniques such as transmission power-based versus SINRbased, and centralized versus distributed method, and further provided various requirements for the efficient resource allocation techniques.…”

Section: B Related Workmentioning

confidence: 99%

Dynamic Spectrum Sharing in 5G Wireless Networks With Full-Duplex Technology: Recent Advances and Research Challenges

Sharma

Bogale

et al. 2018

IEEE Commun. Surv. Tutorials

203

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Full-Duplex (FD) wireless technology enables a radio to transmit and receive on the same frequency band at the same time, and it is considered to be one of the candidate technologies for the fifth generation (5G) of wireless communications due to its advantages including potential doubling of the capacity, reduced end-to-end and feedback delays, improved network secrecy and efficiency, and starting with a detailed overview of FD-enabled DSS, we provide a comprehensive survey of recent advances in this domain. We then highlight several potential techniques for enabling FD operation in DSS wireless systems. Subsequently, we propose a novel communication framework to enable CST in DSS systems by employing a power control-based SI mitigation scheme and carry out the throughput performance analysis of this proposed framework. Finally, we discuss some open research issues and future directions with the objective of stimulating future research efforts in the emerging FD-enabled DSS wireless systems.

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Section: B Related Workmentioning

confidence: 99%

Dynamic Spectrum Sharing in 5G Wireless Networks With Full-Duplex Technology: Recent Advances and Research Challenges

Sharma

Bogale

et al. 2018

IEEE Commun. Surv. Tutorials

203

View full text Add to dashboard Cite

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“…Moreover, the work of this survey paper is also related to the survey papers on various aspects of CRNs, such as spectrum sensing [25]- [30], spectrum decision [31]- [35], resource allocation [36]- [41], security and privacy [42]- [48], MAC protocols [49], [50], routing [51], network coding [52], various applications [53]- [56], to just mention a few. A list of the related survey papers is provided in Table I for further references.…”

Section: B Comparison With Related Survey Articlesmentioning

confidence: 99%

“…2013 [29] A tutorial on kernel-based learning for spectrum sensing in CRNs. 2017 [30] A survey of the applications of spectrum sensing in CR interweave communications.…”

Section: Spectrum Sensingmentioning

confidence: 99%

Spectrum Inference in Cognitive Radio Networks: Algorithms and Applications

Ding

Jiao

Wang

et al. 2018

IEEE Commun. Surv. Tutorials

154

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Abstract-Spectrum inference, also known as spectrum prediction in the literature, is a promising technique of inferring the occupied/free state of radio spectrum from already known/measured spectrum occupancy statistics by effectively exploiting the inherent correlations among them. In the past few years, spectrum inference has gained increasing attention owing to its wide applications in cognitive radio networks (CRNs), ranging from adaptive spectrum sensing, and predictive spectrum mobility, to dynamic spectrum access and smart topology control, to name just a few. In this paper, we provide a comprehensive survey and tutorial on the recent advances in spectrum inference. Specifically, we first present the preliminaries of spectrum inference, including the sources of spectrum occupancy statistics, the models of spectrum usage, and characterize the predictability of spectrum state evolution. By introducing the taxonomy of spectrum inference from a time-frequency-space perspective, we offer an in-depth tutorial on the existing algorithms. Furthermore, we provide a comparative analysis of various spectrum inference algorithms and discuss the metrics of evaluating the efficiency of spectrum inference. We also portray the various potential applications of spectrum inference in CRNs and beyond, with an outlook to the 5th generation mobile communications (5G) and next generation high frequency (HF) communications systems. Last but not least, we highlight the critical research challenges and open issues ahead.

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“…[1][2][3][4] The cognitive radio network (CRN) follows the OSA model in which the cognitive user (CU) periodically senses the spectrum to identify the free/unused channels in specified radio frequency (RF) environment. Among the variety of spectrum sensing techniques available in the reported literature, 7 the energy detector spectrum sensing (EDSS) 8,9 technique is most widespread due to its least complexity among all other available spectrum sensing techniques used in cognitive radio communication systems, and also, its practical implementation is convenient. Among the variety of spectrum sensing techniques available in the reported literature, 7 the energy detector spectrum sensing (EDSS) 8,9 technique is most widespread due to its least complexity among all other available spectrum sensing techniques used in cognitive radio communication systems, and also, its practical implementation is convenient.…”

Section: Introductionmentioning

confidence: 99%

Intelligent threshold selection in fading environment of cognitive radio network: Advances in throughput and total error probability

Kumar

Thakur

Pandit

et al. 2019

Int J Communication

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One of the main challenges of spectrum sensing (SS) in the cognitive radio network (CRN) is selection of threshold for captivating the sensing decision, and such an issue becomes more challenging especially at low signal-to-noise ratio (SNR) because it affects the sensing performance and throughput of cognitive user (CU). However, the sensing decision of individual CU may not be accurate due to fading effects in the sensing environment, and significant improvement is accomplished with the cooperation of users. Therefore, in this paper, we have investigated the performance of energy detector SS (EDSS) technique in the CRN under fading environment with cooperative and noncooperative SS scenario. Further, we have introduced the concept of critical SNR (γ c ) to select the appropriate threshold and based on which the algorithms are proposed to enhance the throughput and reduce the total error (sensing error) probability of CU at different SNR (γ). From the results, we have accomplished that at the low SNR region (γ ≤ γ c ), throughput is maximum with constant false-alarm rate (CFAR) threshold selection approach in the cooperative scenario while in the high SNR region (γ > γ c ), its value is maximum with minimizing the error probability (MEP) threshold selection approach in the noncooperative scenario. Moreover, the sensing error is reduced with cooperation, and threshold selection with MEP approach outperforms CFAR approach for γ ≤ γ c . Further, the proposed approach outperforms the other approaches in terms of throughput and sensing error (total error) probability in the Rayleigh and Nakagami-m fading environments.

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Advances on Spectrum Sensing for Cognitive Radio Networks: Theory and Applications

Cited by 506 publications

References 210 publications

Dynamic Spectrum Sharing in 5G Wireless Networks With Full-Duplex Technology: Recent Advances and Research Challenges

Dynamic Spectrum Sharing in 5G Wireless Networks With Full-Duplex Technology: Recent Advances and Research Challenges

Spectrum Inference in Cognitive Radio Networks: Algorithms and Applications

Intelligent threshold selection in fading environment of cognitive radio network: Advances in throughput and total error probability

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