Architecture Model for Wireless Network Conscious Agent

摘要: Cognitive radios (CRs) use artificial intelligence algorithms to obtain an improved quality of service (QoS). CRs also benefit from meta—cognition that enable them determine the most suitable intelligent algorithm for achieving their operational goals. Examples are used by support vector machines, neural networks and hidden markov models. Each these can be realized in a different manner tasks such as predicting idle state duration channel. The CR benefits jointly using selecting prediction at epoch interest. incorporation meta-cognition furnishes with consciousness. This is because it makes aware its learning mechanisms. consciousness consumes resources i.e. battery memory. resource consumption should reduced enhance CR's available data transmission. discussion this paper proposes meta—cognitive solution reduces associated maintaining proposed incorporates time domain uses information on executing transmission tasks. In addition, integrated multimode CR. Evaluation shows performance improvement transceiver power, computational channel capacity lies range 18.3% – 42.5% , 21.6% 44.8% 9.5% 56.3% average, respectively.