Energy-efficiency performance of wireless cognitive radio sensor network with hard-decision fusion over generalized $$\alpha -\mu$$ fading channels

Nallagonda, Srinivas

doi:10.1007/s11276-023-03350-4

Cited by 9 publications

(2 citation statements)

References 30 publications

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“…Te ideal values for the number of CRSs and detection threshold are also obtained [21] for a number of other network parameters. Examines the CR wireless sensor network's throughput and energy efciency in [22]. More specifcally, conditions afecting the sensing (S) channels that involve both noise and α-μ fading are considered.…”

Section: Related Workmentioning

confidence: 99%

Enhance the Probability of Detection of Cooperative Spectrum Sensing in Cognitive Radio Networks Using Blockchain Technology

Balakumar,

Sendrayan

2023

Journal of Electrical and Computer Engineering

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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 traffic causes congestion in the licensed band for the transmission of signals. Handling this security issue in real time, on top of spectrum sharing, is a challenge in such networks. In order to manage the spectrum and identify MU, blockchain-based CSS is developed in this article. To gauge the efficiency of the proposed topology, performance metrics like sensitivity, node selection, throughput measurement, and energy efficiency are used. This work suggests a unique, easier-to-use CSS method with MU suppression that outperforms the current one. According to simulation studies, the suggested topology can increase the likelihood of MU detection by roughly 15% when 40% of system users are malicious.

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Section: Related Workmentioning

confidence: 99%

Enhance the Probability of Detection of Cooperative Spectrum Sensing in Cognitive Radio Networks Using Blockchain Technology

Balakumar,

Sendrayan

2023

Journal of Electrical and Computer Engineering

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“…Considering that the spectrum shortage problem is caused by insufficient utilization of spectrum resources, cognitive radio (CR) technology is proposed to allow sensors to opportunistically access the channels being underutilized by the primary users (PUs) meanwhile avoiding unreasonable interference to the PU's transmission 1 . Therefore, a CR‐enabled wireless sensor network come into being, named as cognitive wireless sensor networks (CWSNs) 2,3 . The spectrum sensing technology has also become a key function for unauthorized sensors in CWSNs.…”

Section: Introductionmentioning

confidence: 99%

Less sample‐cooperative spectrum sensing against large‐scale Byzantine attack in cognitive wireless sensor networks

Wu,

Dai,

Teng

et al. 2024

Trans Emerging Tel Tech

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Cooperative spectrum sensing (CSS) has emerged as a promising strategy for identifying available spectrum resources by leveraging spatially distributed sensors in cognitive wireless sensor networks (CWSNs). Nevertheless, this open collaborative approach is susceptible to security threats posed by malicious sensors, specifically Byzantine attack, which can significantly undermine CSS accuracy. Moreover, in extensive CWSNs, the CSS process imposes substantial communication overhead on the reporting channel, thereby considerably diminishing cooperative efficiency. To tackle these challenges, this article introduces a refined CSS approach, termed weighted sequential detection (WSD). This method incorporates channel state information to validate the global decision made by the fusion center and assess the trust value of sensors. The trust value based weight is assigned to sensing samples, which are then integrated into a sequential detection framework within a defined time window. This sequential approach prioritizes samples based on descending trust values. Numerical simulation results reveal that the proposed WSD outperforms conventional fusion rules in terms of the error probability, sample size, achievable throughput, and latency, even under varying degrees of Byzantine attack. This innovation signifies a substantial advancement in enhancing the reliability and efficiency of CSS.

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Energy Optimization and Secure Aware Spectrum Allocation Using Hybrid Meta-Heuristic Algorithms in Cognitive Radio Network

Kumar,

Nithyavathy

2024

IETE Journal of Research

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Energy-efficiency performance of wireless cognitive radio sensor network with hard-decision fusion over generalized $$\alpha -\mu$$ fading channels

Cited by 9 publications

References 30 publications

Enhance the Probability of Detection of Cooperative Spectrum Sensing in Cognitive Radio Networks Using Blockchain Technology

Enhance the Probability of Detection of Cooperative Spectrum Sensing in Cognitive Radio Networks Using Blockchain Technology

Less sample‐cooperative spectrum sensing against large‐scale Byzantine attack in cognitive wireless sensor networks

Energy Optimization and Secure Aware Spectrum Allocation Using Hybrid Meta-Heuristic Algorithms in Cognitive Radio Network

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