Metacognitive Radio Engine Design and Standardization

Abstract

In this paper, we provide an overview of how cognitive radio (CR) technology is making its way into the current wireless standards, and we discuss further opportunities for more CR-oriented standardization efforts. Specifically, we discuss how a cognitive engine (CE) can be potentially standardized, and we offer our latest innovations on metacognitive engine (meta-CE) design. The intelligent techniques of a CR are implemented in an agent commonly referred to as a CE. A CE manages the CR's operation. Typically, a CE is based on a primary learning and optimization algorithm that is utilized within the CE. Each of these algorithms has its own strengths and deficiencies depending on the operating scenario that makes some of them more appropriate for specific operating conditions. A meta-CE is an engine that learns which CE is more appropriate to provide the adaptation needed for the operating conditions. To make a meta-CE possible, first, we need a method for characterizing the CE algorithm's performance. Second, we should classify the operating conditions based on the CE algorithm's characteristics in order to determine the most appropriate operating condition. Our results show that, when we use meta-CE techniques, we have about 30% increase in performance compared with using the best individual CE.