Detecting Primary Signals Using Time and Space Model

The advantage of using cognitive radio technology is its ability to adapt and behave to the needs of the application. The adaptability to the application leads cognitive radios with the potential for creating next generation cognitive wireless network. In dynamic spectrum allocation problem, the cognitive radio technology is used to detect the presence of primary user signal so that spectrum will be efficiently utilized by cognitive users (secondary users). To detect the presence of primary user, cognitive radio requires the data related to history of primary signal including time, signal strength (signal will be detected above certain threshold) through detection techniques (energy detectors, matched filter, feature detection, etc.), and finally analyze this data to detect the signal without failure. In this research, a stochastic model is used to detect the primary signal at a given time and space (primary signal decodable area or domain). The proposed time-space model uses Drake’s equation to improve the detection of primary signal.