Enhanced spectrum aggregation based frequency‐band selection routing protocol for cognitive radio ad‐hoc networks

Priya, S.; Kannan, N.

doi:10.1002/cpe.4911

Cited by 3 publications

(2 citation statements)

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“…The proposed protocol requires a localization system to determine the users’ current location. Priya and Kannan [ 16 ] present a frequency-band selection routing protocol with enhanced spectrum aggregation for cognitive radio ad hoc networks. The protocol considers user mobility, spectrum availability, and quality of service to make optimal routing decisions.…”

Section: Related Workmentioning

confidence: 99%

Decision-Making Algorithm with Geographic Mobility for Cognitive Radio

Cervantes-Junco,

Rodriguez-Colina,

Palacios-Luengas

et al. 2024

Sensors

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The proposed novel algorithm named decision-making algorithm with geographic mobility (DMAGM) includes detailed analysis of decision-making for cognitive radio (CR) that considers a multivariable algorithm with geographic mobility (GM). Scarce research work considers the analysis of GM in depth, even though it plays a crucial role to improve communication performance. The DMAGM considerably reduces latency in order to accurately determine the best communication channels and includes GM analysis, which is not addressed in other algorithms found in the literature. The DMAGM was evaluated and validated by simulating a cognitive radio network that comprises a base station (BS), primary users (PUs), and CRs considering random arrivals and disappearance of mobile devices. The proposed algorithm exhibits better performance, through the reduction in latency and computational complexity, than other algorithms used for comparison using 200 channel tests per simulation. The DMAGM significantly reduces the decision-making process from 12.77% to 94.27% compared with ATDDiM, FAHP, AHP, and Dijkstra algorithms in terms of latency reduction. An improved version of the DMAGM is also proposed where feedback of the output is incorporated. This version is named feedback-decision-making algorithm with geographic mobility (FDMAGM), and it shows that a feedback system has the advantage of being able to continually adjust and adapt based on the feedback received. In addition, the feedback version helps to identify and correct problems, which can be beneficial in situations where the quality of communication is critical. Despite the fact that the FDMAGM may take longer than the DMAGM to calculate the best communication channel, constant feedback improves efficiency and effectiveness over time. Both the DMAGM and the FDMAGM improve performance in practical scenarios, the former in terms of latency and the latter in terms of accuracy and stability.

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Section: Related Workmentioning

confidence: 99%

Decision-Making Algorithm with Geographic Mobility for Cognitive Radio

Cervantes-Junco,

Rodriguez-Colina,

Palacios-Luengas

et al. 2024

Sensors

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“…Dynamic spectrum allocation is the primary principle of Cognitive Radio (CR) technology. It strives to correct the inefficiency in the utilization of the spectrum proposed earlier by Mitola 5 . The spectrum is effectively utilized by means of the CRs, which plug the holes of the radio spectrum with SU or unlicensed users.…”

Section: Introductionmentioning

confidence: 99%

Support Vector Machine based spectrum handoff scheme for seamless handover in Cognitive Radio Networks

Iyer¹,

Velmurugan

Periasamy

et al. 2022

Concurrency and Computation

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Summary The advancements in wireless communication go in leaps and bounds ushering in due attention to spectrum sharing. Spectrum scarcity is one of the major limitations causing hardships in the existing wireless networks. Cognitive Radio Networks (CRNs) emerge as a solution to tide over such humps. It prompts the secondary user (SU) to look out for unused spectrum and utilize them. The CRN helps the SU by permitting it to switch over to unused portions of the spectrum. When a primary user (PU) claims back the spectrum, SU is obliged to perform a spectrum handoff. The SU decides the type of policy to be chosen for the handoff. Such a decision‐making step during the handoff of the spectrum is imperative only if a changing policy is required. In this research work, Artificial Neural Networks (ANNs), Logistic Regression and Support Vector Machine (SVM) are proposed and implemented for a seamless handoff in CRN. From the experimental verifications, it is observed that the training accuracy is 97.9% and 97.6% for ANN and SVM, respectively. But during the actual phase, SVM to a certain extent performed better. This is due to the convergence nature of SVM on global minima.

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A Study of Recent Security Attacks on Cognitive Radio Ad Hoc Networks (CRAHNs)

Dansana

Behera

2020

Advances in Intelligent Systems and Computing

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Enhanced spectrum aggregation based frequency‐band selection routing protocol for cognitive radio ad‐hoc networks

Cited by 3 publications

References 20 publications

Decision-Making Algorithm with Geographic Mobility for Cognitive Radio

Decision-Making Algorithm with Geographic Mobility for Cognitive Radio

Support Vector Machine based spectrum handoff scheme for seamless handover in Cognitive Radio Networks

A Study of Recent Security Attacks on Cognitive Radio Ad Hoc Networks (CRAHNs)

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