Modelo AHP-VIKOR para handoff espectral en redes de radio cognitiva

Hernández, César; Páez, Ingrid; Giral, Diego

doi:10.14483/udistrital.jour.tecnura.2015.3.a02

Cited by 12 publications

(12 citation statements)

References 17 publications

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“…According to this, MCDM is a mathematical tool adapted to model the SH process. Various MCDM methods have been proposed in the literature about SH, such as, SAW [32], [33], TOPSIS [32], [34], MEW [35], [36], GRA [37], [38], ELECTRE [39], Weighted Markov Chain (WMC) [40] and VIKOR [37], [41]. Authors on [31] present an extensive comparative study about the seven MCDM methods previously mentioned.…”

Section: Related Workmentioning

confidence: 99%

“…The MCDM methods are a proper mathematical tool to model the SH process when multiple variables are involved demonstrating to be an effective alternative to evaluate and select the SO, therefore, these have been widely used for SH as shown in the literature review, [26]- [30]. The chosen algorithms are, SAW [32], [33], TOPSIS [32], [34], MEW [35], [36], VIKOR [37], [41] y AHP [26], [27], [38], [42], [43].…”

Section: Sh Algorithms Selectionmentioning

confidence: 99%

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Multivariable adaptive handoff spectral model for cognitive radio networks

Hernández¹,

Martínez²,

Rodríguez-Colina³

2017

ces

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This work presents a multivariable adaptive spectrum handoff model for cognitive radio networks that allows improving secondary user's spectrum mobility from the intelligent selection of spectrum opportunities called MAPMFF. Four algorithms for decision making during a spectrum handoff, were developed with different approaches, fuzzy, feedback statistics, predictive and multichannel, which make up the MAPMFF proposed model. The best spectrum opportunities were selected dynamically based on the following decision criteria, the probability of channel availability, estimated time of channel availability, Signal-to-interference-plusnoise ratio, and bandwidth, which were determined through the modified Delphi method and corresponding weights were calculated through the developed FFAHP algorithm. In order to assess the performance of the developed algorithms, a comparative analysis was made between these algorithms and the most relevant spectrum handoff algorithms in the current literature. Unlike other related papers, benchmarking was validated through a trace of real spectrum occupation data captured in the frequency GSM band, which characterizes the real behavior of primary users. In the validation phase, four assessment scenarios were proposed to 40 Cesar Hernández et al. consider, two kind of applications, real-time and best-effort; two traffic case scenarios, high and low and, ten evaluation metrics, number of handoff, number of failed handoff, bandwidth, delay, throughput, fairness, number of handoff without interference, number of handoff with interference, number of perfect handoff and number of anticipated handoff. The main contribution of this work is the development of an adaptive spectral model (MAPMFF) with excellent performance according to the results of validation with real occupation spectral data in 4 different scenarios, with four types of traffic, and under ten evaluation metrics. Consequently, the impact reached by the MAPMFF model is the improvement in the quality of service parameters for mobile communications. The proposed multi-model selects the best spectrum handoff algorithm, among the four models developed in this work. This is according to the spectrum characteristics and requirements of the secondary user, providing an efficient and effective process of frequency channel selection. Then, the MAPMFF model behaves as an expert system when inferring from data known from a wireless application and spectral occupation the best spectral handoff algorithm. This is in order to analyze and decide which spectral opportunity is the appropriated to the user requirements by an inference engine. The results of the comparative analysis with other spectrum handoff algorithms show that the MAPMFF model provides the best performance in the ten evaluation metrics for the four proposed scenarios. According to the obtained results, the proposed model has a low average handoff rate, a high percentage of average throughput and average bandwidth, and a low level of average delay.

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Section: Related Workmentioning

confidence: 99%

Section: Sh Algorithms Selectionmentioning

confidence: 99%

Multivariable adaptive handoff spectral model for cognitive radio networks

Hernández¹,

Martínez²,

Rodríguez-Colina³

2017

ces

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“…"VIKOR method assumes that every alternative has to be evaluated based on every criterion function and the classification could be developed through a comparison among the measures that are closer to the ideal alternative" [47][48][49]. VIKOR was developed to fulfill the optimization of complex systems with multiple criteria, hence, it is able to delimit the compromise on a ranking list, still in presence of the conflicting criteria what makes an algorithm suitable to make decisions in SA [50].…”

Section: Vikormentioning

confidence: 99%

“…VIKOR algorithm follows the steps described in [25,42,46,48]. For each decision criterion, the best and the worst value are delimited taking into consideration if they are profits or costs.…”

Section: Vikormentioning

confidence: 99%

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Fuzzy feedback algorithm for the spectral handoff in cognitive radio networks

Suárez

Martínez

Rodríguez-Colina

2016

Rev. Fac. Ing. Univ. Antioquia

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This work proposes a feedback algorithm based on a Fuzzy AnalyticalHierarchical Process Method (FAHP) to improve decision making for the spectral handoff. We named it Feedback FAHP (FFAHP). To assess the performance level of the developed algorithms, a comparative analysis was made between the proposed FFAHP algorithm and the most relevant spectrum handoff algorithms in the current literature. These algorithms were assessed with the same decision criteria, which are, the probability of channel availability, estimated channel time availability, the signal to interference plus noise ratio and bandwidth. Unlike other related papers, benchmarking was validated through a trace of real spectrum occupation data captured in the frequency band GSM and Wi-Fi, which model the real behavior of primary users. In the validation phase, eight assessment scenarios were proposed to consider, two types of networks: GSM and Wi-Fi, two kinds of applications: real-time and best-effort, two traffic levels: high and low, and five evaluation metrics: number of handoffs, the number of failed handoff, bandwidth, delay, throughput. The results show that the proposed FFAHP Algorithm provides a performance improvement. The FFAHP Algorithm supplies an efficient and effective process for selecting frequency channels. The results indicate that the proposed FFAHP Algorithm provides a performance improvement. The FFAHP Algorithm supplies an efficient and effective method for selecting frequency channels. The results also show that the FFAHP Algorithm has a low average rate of handoffs, an effective use of the bandwidth, low delay and a high level of throughput; all these combined with the fact that the feedback implemented, stabilizes the system avoiding loops with consecutive hops to alternate frequencies. RESUMEN: Este trabajo propone un algoritmo difuso realimentado basado en el métodoFuzzy Analytical Hierarchical Process (FAHP) para mejorar la toma de decisiones para el handoff espectral. El algoritmo propuesto es denominado Feedback FAHP (FFAHP). Para evaluar el nivel de desempeño de los algoritmos desarrollados se realiza un análisis comparativo entre el algoritmo FFAHP propuesto y los algoritmos de handoff espectral más relevantes en la literatura actual. Estos algoritmos son diseñados con los mismos criterios de decisión, los cuales son: probabilidad de disponibilidad del canal, tiempo estimado de disponibilidad del canal, relación señal a ruido más interferencia y ancho de banda. A diferencia de los trabajos relacionados, la evaluación comparativa se validó a través de una traza de datos reales de ocupación espectral capturados en la banda de frecuencia GSM y Wi-Fi, que modelan el comportamiento real de los usuarios primarios. En la fase de validación se propusieron ocho escenarios de evaluación, al considerar, dos tipos de redes: GSM y Wi-Fi, dos clases de aplicaciones: tiempo-real y mejor-esfuerzo, dos niveles de tráfico: alto y bajo, y cinco métricas de evaluación: número de handoff, número de handoff fallidos, ancho de band...

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