Fuzzy feedback algorithm for the spectral handoff in cognitive radio networks

Suárez, César Augusto Hernández; Martínez, Luis Fernando Pedraza; Rodríguez-Colina, Enrique

doi:10.17533/udea.redin.n81a05

Cited by 13 publications

(23 citation statements)

References 60 publications

(49 reference statements)

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“…To analyze the decision-making process, two MCDM techniques are implemented. The chosen strategies are: Feedback Fuzzy Analytical Hierarchical Process (FFAHP) [17,28] and Simple Additive Weighting (SAW) [17,27]. Furthermore, the analysis is carried out according to the class service: real-time (RT) and best effort (BE).…”

Section: Rowmentioning

confidence: 99%

“…The FFAHP algorithm (Feedback FAHP) proposes the feedback of the information from previous assessments based on the FAHP method [28]. The FAHP algorithm uses fuzzy logic as a tool which is particularly adequate to make decisions in scenarios where the inputs are often uncertain or inaccurate.…”

Section: Ffahpmentioning

confidence: 99%

“…In essence, the FAHP algorithm uses the same methodology of the AHP algorithm [17]. However, fuzzy logic supports in handling the subjectivity and uncertainty generated during the assessment process [28]. After normalization, the FAHP algorithm states that the weight vector is given by (1).…”

Section: Ffahpmentioning

confidence: 99%

“…(2), while (3) is used for BE applications. The coefficients of each of the equations are taken from [28]. The Table 9…”

Section: Ffahpmentioning

confidence: 99%

“…For the analysis of the decision making proposed, a collaborative algorithm is designed to segment the matrix according to five levels of collaboration. The decision-making process is based on two multi-criteria (MCDM) techniques: Feedback Fuzzy Analytical Hierarchical Process (FFAHP) and Simple Additive Weighting (SAW) [2,15,16,[27][28][29].…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of the Failed Handoff Rate in Collaborative Wireless Networks

Giral¹,

Hernández²,

Rodríguez-Colina³

2020

Preprint

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Cognitive radio is an essential technology to overcome fixed spectrum allocation problems and improve its use through dynamic spectrum access techniques. Spectral decision-making is a function of the cognitive cycle that aims to choose the best spectral alternative among a set of finite possibilities. An inadequate process of decision-making can significantly affect the network parameters. Therefore, it is important to determine the best strategy and if this decision making should be collaborative. The present research analyzes the performance of failed handoff rate according to the amount of information shared between secondary users. The aforementioned information corresponds to the spectral occupancy for the GSM frequency band, that is characterized by a set of users and five levels of collaboration, 10%, 20%, 50%, 80% and 100%, where each level represents the percentage of users are part of the training model implemented. The decision-making process is carried out by using two multi-criteria techniques: Feedback Fuzzy Analytical Hierarchical Process (FFAHP) and Simple Additive Weighting (SAW). Based on the obtained percentage ratios and the information shared, it is determined that for the given number of failed handoffs, the level of collaboration that leads to efficient results is between 20% and 50%.

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Section: Rowmentioning

confidence: 99%

Section: Ffahpmentioning

confidence: 99%

Section: Ffahpmentioning

confidence: 99%

“…(2), while (3) is used for BE applications. The coefficients of each of the equations are taken from [28]. The Table 9…”

Section: Ffahpmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Evaluation of the Failed Handoff Rate in Collaborative Wireless Networks

Giral¹,

Hernández²,

Rodríguez-Colina³

2020

Preprint

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Spectral decision for cognitive radio networks in a multi-user environment

Giral¹,

Hernández²,

Salgado³

2021

Heliyon

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Cognitive radio networks promote better spectral efficiency of the electric radio spectrum. The vast majority of current spectral decision models for cognitive radio networks evaluate their performance based on a single secondary user. In reality, the network can experience multiple requests from spectral opportunities. Based on this, the intent of this article is to present and evaluate a spectral decision model for cognitive radio networks in a multi-user environment taking into account the effect of the decisions of the SU on the usefulness of the other SU. To achieve this, a spectral decision model was developed that allows secondary users to share relevant information before accessing the spectrum so that they can select the most appropriate spectral opportunities. The evaluation and validation of the model was performed using three multicriteria decision-making algorithms under the metric of the number of total handoffs in a conventional scenario and a real scenario, in the conventional scenario, only users that match the input of the multiuser module are included; in the real scenario, in addition to the conventional users, users that enter and leave at random times are included, a feature that alters the models for estimating the behavior of the radio environment. The results show better performance of the TOPSIS algorithm over VIKOR and SAW. The most important contribution of this work is the evaluation of the performance of the spectral decision algorithms implemented in a multi-user environment that allows multiple access and exchange of information between users, with experimental spectral occupation data.

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Evaluation of the performance of a collaborative proposal of multiple access in cognitive radio networks

Ramı́rez

Suárez

Martínez

2021

Heliyon

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Cognitive radio networks (CRN) allow for an increase in spectral efficiency and performance of today's wireless networks. Currently, multiple proposals exist in the area of spectral decision-making and mobility; however, very few evaluate the impact of collaboration between secondary users and the performance of spectrum access by many secondary users. Unlike existing works, this article provides a comprehensive quantitative analysis of the performance of CRN taking into account access to the spectrum simultaneously by multiple users and decision making based on collaboration through the exchange of information between nearby secondary users. This proposal is developed through the implementation of four modules: Input Module, Multi-user Module, Collaborative module and Decision-making module, where the results are evaluated comparatively through the handoff rate generated with two multicriteria techniques: Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Multi-Criteria Optimization and Compromise Solution (VIKOR). The evaluation is carried out taking into account three levels of collaboration, three multi-user access scenarios, and two multi-criteria techniques for a total of 18 simulation scenarios. The results obtained show the importance of implementing collaboration strategies, as for multi-user access, the number of handoffs increases as the number of serial users increases. TOPSIS presented the best results in 76 % of the analyzed cases where VIKOR generated a smaller number of handoffs; TOPSIS maintained good performance with differences not exceeding 90 handoffs.

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Fuzzy feedback algorithm for the spectral handoff in cognitive radio networks

Cited by 13 publications

References 60 publications

Evaluation of the Failed Handoff Rate in Collaborative Wireless Networks

Evaluation of the Failed Handoff Rate in Collaborative Wireless Networks

Spectral decision for cognitive radio networks in a multi-user environment

Evaluation of the performance of a collaborative proposal of multiple access in cognitive radio networks

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