Failed handoffs in collaborative Wi-Fi networks

Hernández, César; Giral, Diego; Salgado, Camila

doi:10.12928/telkomnika.v18i2.14894

Cited by 3 publications

(3 citation statements)

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“…Another method to improve Wi-Fi performance is to upgrade the existing antenna with a microstrip antenna [13], [14]. TOPSIS and VIKOR algorithms were investigated in the Wi-Fi radio spectrum to address handoff failures [15].…”

Section: Figure 1 Radio Access Technology On Heterogeneous Networkmentioning

confidence: 99%

Adaptive Wi-Fi offloading schemes in heterogeneous networks, the survey

Ruliyanta

Ahmad

Isa

2022

IJEECS

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At present, the need for data traffic is experiencing tremendous growth. The growth of smartphones technology offers new applications. On the other hand, the growth in cellular network access infrastructure has not been able to keep up with the increasing demand for data package services. For this reason, Wi-Fi offloading is needed, namely cellular users, using Wi-Fi access for their data needs. In 2016, global data communication traffic growth reached 63%. Many researchers have proposed the adaptive wireless fidelity (Wi-Fi) offloading (AAWO) algorithm to transfer data on heterogeneous networks. In this study, the proposed adaptive incentive scheme is classified, to obtain an adaptive scheme based on cost, energy, service quality, and others. From the survey results shown, there is no proposed adaptive algorithm based on the quality of experience (QoE). This provides an opportunity for further research where the Wi-Fi offloading scheme uses the perspective user or user experient options. In addition, open research uses artificial intelligence and machine learning methods as adaptive methods.

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Section: Figure 1 Radio Access Technology On Heterogeneous Networkmentioning

confidence: 99%

Adaptive Wi-Fi offloading schemes in heterogeneous networks, the survey

Ruliyanta

Ahmad

Isa

2022

IJEECS

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“…This is achieved through a management model known as the cognitive cycle [4]. The process of a SU changing its operation frequency is called spectral mobility [5], [6] which gives way to a new type of handoff in CRN (spectral handoff) [7]. To characterize spectral mobility in CRN, the process of SU decision-making needs to be analyzed in terms of spectrum variation and the actions performed by ISSN: 2088-8708 …”

Section: Introductionmentioning

confidence: 99%

Analysis and assessment software for multi-user collaborative cognitive radio networks

Giral

Hernández

Sarmiento

2022

IJECE

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<span>Computer simulations are without a doubt a useful methodology that allows to explore research queries and develop prototypes at lower costs and timeframes than those required in hardware processes. The simulation tools used in cognitive radio networks (CRN) are undergoing an active process. Currently, there is no stable simulator that enables to characterize every element of the cognitive cycle and the available tools are a framework for discrete-event software. This work presents the spectral mobility simulator in CRN called “App MultiColl-DCRN”, developed with MATLAB’s app designer. In contrast with other frameworks, the simulator uses real spectral occupancy data and simultaneously analyzes features regarding spectral mobility, decision-making, multi-user access, collaborative scenarios and decentralized architectures. Performance metrics include bandwidth, throughput level, number of failed handoffs, number of total handoffs, number of handoffs with interference, number of anticipated handoffs and number of perfect handoffs. The assessment of the simulator involves three scenarios: the first and second scenarios present a collaborative structure using the multi-criteria optimization and compromise solution (VIKOR) decision-making model and the naïve Bayes prediction technique respectively. The third scenario presents a multi-user structure and uses simple additive weighting (SAW) as a decision-making technique. The present development represents a contribution in the cognitive radio network field since there is currently no software with the same features.</span>

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“…Lo anterior se logra a partir de un modelo de gestión denominado ciclo cognitivo, el cual es una estructura de radio que puede reconfigurarse mediante un proceso continuo de conciencia (tanto de sí mismo como del mundo exterior), percepción, razonamiento y toma de decisiones (Haykin, 2005). El ciclo cognitivo se caracteriza por cuatro funciones principales: detección del espectro, decisión de espectro, movilidad espectral y compartición de espectro (Giral et al, 2020;Hernandez et al, 2020;Hernandez et al, 2020a).…”

Section: Introductionunclassified