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Currently, there are saturated frequency bands that affect the quality of service for new users. Cognitive radio provides an alternative solution to this problem through dynamic spectrum access. However, the solutions proposed in the current literature are focused on a centralized network and do not allow demonstrating the behavior in a multi-user environment, much less the effect that cooperation between secondary users can have. This article establishes a decision-making model for the best spectral opportunity selection with a cooperative approach in decentralized cognitive radio networks and contrasts its results with three multi-criteria decision-making algorithms: SAW, TOPSIS, and VIKOR. So, this research suggests a cooperative decision-making model based on four main modules. (1) a collaborative module for the exchange of information between SU; (2) a module for PU characterization; (3) a module of the probability of SU arrival; and (4) the SO feedback selection module. The results are obtained through simulations fed with experimental spectral occupancy data captured in a measurement campaign. Handoff and throughput were used as evaluation metrics, along with five levels of collaboration: 10%, 20%, 50%, 80%, and 100%, and eight different scenarios based on the type of network: GSM and Wi-Fi, the application type: real-time and best-effort, and the level of traffic: high and low. The contribution of this study lies in the fact that no current work includes the following relevant aspects for an adequate validation and evaluation of this proposal: First, the consideration of a decentralized cognitive radio network; second, the decision-making with cooperative strategies; third, different techniques for SO selection; fourth, the validation and evaluation with experimental spectral occupancy data captured in measurement campaigns; finally, the performance analysis in diverse networks, traffic levels, and types of applications., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

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., Competing Interests: The authors declare no conflict of interest., (© 2021 The Author(s).)