Intelligent Algorithm for Spectrum Mobility in Cognitive Wireless Networks

Salgado, Camila; Hernández, César; Molina, Vitor Eduardo; Beltran-Molina, Ferney A.

doi:10.1016/j.procs.2016.04.126

Cited by 13 publications

(9 citation statements)

References 14 publications

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“…Then the handover execution process is executed with the help of the shift module of CR-Site. [16]. The authors have utilised multiple-criteria decisionmaking approach to select the optimal channel selection in prior, which can be utilised by the CR-node to perform the channel handover.…”

Section: Invariantmentioning

confidence: 99%

“…Nejatian et al [15] have proposed a proactive channel switching scheme for Cognitive Radio-Mobile Adhoc Networks (CR-MANETs) considering SU mobility pattern. A fuzzy logic inspired channel selection procedure for efficient handover in cognitive radio based networks has been proposed by salgado et al [16]. In another research work, Ahmed et al [17] have proposed handover decision-making process using Primary User (PU) activity and Signal-To-Noise-Plus-Interference Ratio SINR as handover decision parameters along with optimal channel selection.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, these handover schemes have not addressed the two important phases of any spectrum handover, which are spectrum measurement and handover execution [18]. If we analyze the proactive handover schemes [15][16][17] then the problem with these handover schemes is that they have not been designed keeping in view the challenging nature of syntactic interoperability within high-speed cellular based vehicular networks.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Emotion-controlled spectrum mobility scheme for efficient syntactic interoperability in cognitive radio-based unmanned vehicles

Riaz

Rathore

Sohail

et al. 2020

Computer Communications

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Section: Invariantmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Emotion-controlled spectrum mobility scheme for efficient syntactic interoperability in cognitive radio-based unmanned vehicles

Riaz

Rathore

Sohail

et al. 2020

Computer Communications

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“…The proposed work comprises of developing a cognitive mobile terminal which is capable of sensing the environment and establishing connections based on the availability of the primary user (PU) thereby resolves the problems caused by switching and the high interference rates occurring during data transmission [13].The primary part in our work is using Genetic Algorithm (GA) with cuckoo search for handoff decision making, thereby optimizing fuzzy logic membership functions and which is new form of hybrid approach [14]. This work involves the usage of a new multi criteria kind of hybrid handoff strategy with cognitive ability to switch based on network conditions and availability of channel [15].…”

Section: Proposed Systemmentioning

confidence: 99%

Ingenious Method for Conducive Handoff Appliance in Cognitive Radio Networks

Dhivya

Ramaswami

2018

IJECE

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Wireless communications deployed in the current epoch claims ceaseless connection among its users thereby leading to the investigation of Cognitive Radio Networks (CRN) which enables to make use of unallocated spectrum optimally and provides uninterrupted connection. Establishing interminable connectivity during the handoff process in spectrum mobility of CRN is a challenging task. This paper elucidates the optimization of handoff process carried out in CRN by incorporating an intelligent method. This includes fuzzy logic wherein the handoff parameters are processed thereby indicating the need of handoff. The proffered method also comprises of a part of genetic algorithm which yields fitness value for reducing the handoff occurrences and enhancing the overall performance of the system is promoted using cuckoo search which decides the mobile node from which the handoff process has to initiate based on the priority generated. This technique ensures that decision is taken ahead of link failure rather than range failure which are the key point in comparison to the existing system. Results obtained through the simulation are satisfactory in terms of delay, throughput, number of failed handoff and handoffs performed in comparison to the existing fuzzy based handoff process in CRN.

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“…To achieve this there is a need for artificial intelligence algorithms and techniques (Bayrakdar & Çalhan, 2018), as well as machine learning (A. M., Matyjas, Hu, & Kumar, 2017;Koushik, Hu, & Kumar, 2018), and multi-criteria decisionmaking methods (Hernández, Giral, & Santa, 2015;Salgado, Hernandez, Molina, & Beltran-Molina, 2016), among others. Some examples include particle swarm optimization (Agrawal, Tyagi, & Singh, 2018;Alhammadi, Roslee, & Alias, 2017), real time spectrum transfer (Chakraborty & Misra, 2015), and fuzzy logic (Javed & Naeem, 2018).…”

Section: Introductionmentioning

confidence: 99%

Optimal value of past samples for decision making in cognitive radio networks

Estupiñan

Suárez

Ramírez

2020

Tecnura

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Contexto: El modelado y predicción del uso del espectro por parte de los PU es un aspecto importante para reducir la interferencia entre los SU y PU, y mejorar el desempeño de la decisión espectral. Lo anterior requiere de información espectral pasada, que permita al algoritmo modelar el comportamiento del PU. Objetivo: Determinar el valor óptimo de muestras pasadas y tiempo de recalculo de criterios de decisión, para los algoritmos de toma de decisiones en redes de radio cognitiva. Metodología: Se realizan varios experimentos de simulación a partir del algoritmo FFAHP, en dos diferentes enfoques, tiempo-real y mejor-esfuerzo, con tráfico alto y bajo, en la banda de frecuencia GSM. Se realiza un análisis estadístico de los datos obtenidos, variando los parámetros de time range, mientras criteria time permanece constante, y viceversa. Resultados: Para tráfico alto es suficiente con tomar 1800 muestras anteriores para calcular el valor inicial de los parámetros y actualizarlos cada 10 minutos (1800). Si el tráfico es bajo es suficiente con tomar 5400 muestras anteriores para calcular el valor inicial de los parámetros y actualizarlos cada 10 minutos (1800). Conclusiones: No es necesario un número elevado de muestras anteriores para determinar el valor inicial de los parámetros de decisión para obtener un buen desempeño de la tasa de handoff, así como tampoco lo es para la actualización de los mismos, para un tráfico correspondiente a la banda de frecuencia GSM. Financiamiento: El presente trabajo es un resultado de un proyecto de investigación financiado por el Centro de Investigaciones y Desarrollo Científico de la Universidad Distrital Francisco José de Caldas.

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Intelligent Algorithm for Spectrum Mobility in Cognitive Wireless Networks

Cited by 13 publications

References 14 publications

Emotion-controlled spectrum mobility scheme for efficient syntactic interoperability in cognitive radio-based unmanned vehicles

Emotion-controlled spectrum mobility scheme for efficient syntactic interoperability in cognitive radio-based unmanned vehicles

Ingenious Method for Conducive Handoff Appliance in Cognitive Radio Networks

Optimal value of past samples for decision making in cognitive radio networks

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