This article draws a general retrospective view on the first 10 years of cognitive radio (CR). More specifically, we\r\nexplore in this article decision making and learning for CR from an equipment perspective. Thus, this article depicts\r\nthe main decision making problems addressed by the community as general dynamic configuration adaptation\r\n(DCA) problems and discuss the suggested solution proposed in the literature to tackle them. Within this\r\nframework dynamic spectrum management is briefly introduced as a specific instantiation of DCA problems. We\r\nidentified, in our analysis study, three dimensions of constrains: the environmentââ?¬â?¢s, the equipmentââ?¬â?¢s and the userââ?¬â?¢s\r\nrelated constrains. Moreover, we define and use the notion of a priori knowledge, to show that the tackled\r\nchallenges by the radio community during first 10 years of CR to solve decision making problems have often the\r\nsame design space, however they differ by the a priori knowledge they assume available. Consequently, we\r\nsuggest in this article, the ââ?¬Å?a priori knowledgeââ?¬Â as a classification criteria to discriminate the main proposed\r\ntechniques in the literature to solve configuration adaptation decision making problems. We finally discuss the\r\nimpact of sensing errors on the decision making process as a prospective analysis.
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