On optimal fuzzy c-means clustering for energy efficient cooperative spectrum sensing in cognitive radio networks

Maity, Santi P.; Chatterjee, Subhankar; Acharya, Tamaghna

doi:10.1016/j.dsp.2015.10.006

Cited by 55 publications

(23 citation statements)

References 20 publications

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“…The proposed multiclass hypothesis problem in CSS is addressed using meta heuristic approaches, a hybridization platform in fuzzy functions, and DE optimization, a complex search technique. The existing literature is also rich in the use of various meta heuristic approaches in addressing the CSS problem to achieve a low cost and tractable solution, where classical optimization techniques fail to offer solutions due to lack of well‐defined analytical form of the optimization problem and/or involvement of large number of variables . Furthermore, a constrained optimization problem is addressed in this work, where the CSS performance is met through the target detection and false probability rate.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…The existing literature is also rich in the use of various meta heuristic approaches in addressing the CSS problem 3,4 to achieve a low cost and tractable solution, where classical optimization techniques fail to offer solutions due to lack of well-defined analytical form of the optimization problem and/or involvement of large number of variables. 40 Furthermore, a constrained optimization problem is addressed in this work, where the CSS performance is met through the target detection and false probability rate. The objective function is not directly related with the CSS problem.…”

Section: Confidence Analysis On Performancementioning

confidence: 99%

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Joint cooperative spectrum sensing and primary user emulation attack detection in cognitive radio networks using fuzzy conditional entropy maximization

Banerjee

Maity

2019

Trans Emerging Tel Tech

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Cooperative spectrum sensing (CSS) in cognitive radio system shows improved performance on spectrum sensing but, at the same time, faces a common threat called primary user emulation attack (PUEA) that impersonates the primary user (PU). This work explores joint PU and PUEA detection on CSS as a multiclass hypothesis using fuzzy conditional entropy maximization. To meet the goal, a multithreshold approach is suggested using a constrained differential evolution algorithm search to determine an optimal set of fuzzy function parameters, which maximizes the conditional entropy on the energy values. The proposed work also investigates the performance of CSS in presence of a group of malicious users (as PUEA), which generates signals and directly sends the same to the fusion center. Numerical results through simulation illustrate the efficacy of the proposed scheme in terms of both reliable PU detection in presence or absence of PUEA/malicious user and separate detection of falsifying PU and energy consumption in CSS. Simulation results show that the proposed scheme offers ∼17.54% and ∼39.39% higher detection probability of PU over the existing works in presence of PUEA.

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Section: Numerical Resultsmentioning

confidence: 99%

Section: Confidence Analysis On Performancementioning

confidence: 99%

Joint cooperative spectrum sensing and primary user emulation attack detection in cognitive radio networks using fuzzy conditional entropy maximization

Banerjee

Maity

2019

Trans Emerging Tel Tech

Self Cite

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“…Authors claim that the proposed strategy performs better than existing schemes in terms of accuracy in sensing the right channel, handoff latency, and energy consumption. The authors of [52] projected a reactive handoff scheme for Zigbee in which a CRU can access various channels via incessantly sensing and spectrum handoff. The presented sensing and handoff technique provides better results in a situation where the noise is at a minimal level.…”

Section: Reactive Handoffmentioning

confidence: 99%

“…Since the fuzzy-based scheme has no BCs, the handoff delay can be maximized when the channel underutilization is at its minimal level. DFHC [18], M/G/1 [21] and Zigbee [52] are reactive handoff schemes with no channel backup facility, therefore, the handoff delay is at maximum level and the channel underutilization is at its minimal level. DSA [53] is a hybrid handoff scheme which is considered as a middle course between proactive and reactive handoff schemes.…”

Section: Hybrid Handoffmentioning

confidence: 99%

Primary User Traffic Pattern Based Opportunistic Spectrum Handoff in Cognitive Radio Networks

et al. 2020

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Through the expeditious expansion of the wireless network, the unlicensed bandwidth-based devices are growing substantially as compared to the present vacant bandwidth. Cognitive radio networks present a proficient solution to the spectrum shortage diminution hitch by allowing the usage of the vacant part of the spectrum that is not currently in use of the Primary User licensed bandwidth to the secondary user or cognitive radio user. Spectrum management procedure in cognitive radio network comprises of spectrum sharing, sensing and handoff. Spectrum handoff plays a vital role in spectrum management and primarily focuses on single handoff strategies. This paper presents a primary user traffic pattern-based opportunistic spectrum handoff (PUTPOSH) approach to use in the cognitive radio networks. PUTPOSH permits a secondary user to sense the arrival of a primary user and use an opportunistic handoff scheme. The opportunistic handoff scheme firstly detects the arrival of the primary users by energy detection sensing and secondly, it allows a cognitive radio user to decide whether to do handoff or not contingent upon the overall service time to reduce the unused handoffs. The handoffs can either be reactive or proactive based on the arrival rate of the primary user. The simulation results show that the presented PUTPOSH approach (a) minimizes the number of handoffs and the overall service time, and (b) maintains the channel utilization and throughput of the system at a maximal point.

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“…In recent years, machine learning has developed rapidly, which also provides a new idea for spectrum sensing. Spectrum sensing can be considered as a problem of two classifications that is whether the PU exists [18][19][20].…”

Section: Related Workmentioning

confidence: 99%

A cooperative spectrum sensing method based on information geometry and fuzzy c-means clustering algorithm

Zhang

Wang

et al. 2019

J Wireless Com Network

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To improve spectrum sensing performance, a cooperative spectrum sensing method based on information geometry and fuzzy c-means clustering algorithm is proposed in this paper. In the process of signal feature extraction, a feature extraction method combining decomposition, recombination, and information geometry is proposed. First, to improve the spectrum sensing performance when the number of cooperative secondary users is small, the signals collected by the secondary users are split and reorganized, thereby logically increasing the number of cooperative secondary users. Then, in order to visually analyze the signal detection problem, the information geometry theory is used to map the split and recombine signals onto the manifold, thereby transforming the signal detection problem into a geometric problem. Further, use geometric tools to extract the corresponding statistical characteristics of the signal. Finally, according to the extracted features, the appropriate classifier is trained by the fuzzy c-means clustering algorithm and used for spectrum sensing, thus avoiding complex threshold derivation. In the simulation results and performance analysis section, the experimental results were further analyzed, and the results show that the proposed method can effectively improve the spectrum sensing performance.

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On optimal fuzzy c-means clustering for energy efficient cooperative spectrum sensing in cognitive radio networks

Cited by 55 publications

References 20 publications

Joint cooperative spectrum sensing and primary user emulation attack detection in cognitive radio networks using fuzzy conditional entropy maximization

Joint cooperative spectrum sensing and primary user emulation attack detection in cognitive radio networks using fuzzy conditional entropy maximization

Primary User Traffic Pattern Based Opportunistic Spectrum Handoff in Cognitive Radio Networks

A cooperative spectrum sensing method based on information geometry and fuzzy c-means clustering algorithm

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