Algorithms for decision making in wireless cognitive networks: Review

Abstract

The objective of this article is to present a review of techniques based on artificial intelligence for the decision-making process in cognitive radio networks. The cognitive radio networks emerged as a solution to solve the problems of fixed allocation and scarcity of spectrum, work with a management model called the cognitive cycle. Decision making is key in this cycle since it allows to more appropriately selecting the spectral opportunity. From the current literature, strategies that implement machine learning, bioinspired algorithms, game theory and consensus algorithms are analyzed. Finally, this document presents the challenges for the decision-making process, which highlights the need to continue taking advantage of the advances in artificial intelligence to obtain better results. However, the strategies must be scalable to facilitate the computational load and being able to solve more complex problems.