Cooperative discriminant analysis based spectrum sensing using optimum fusion rule

Cognitive radio is a potential technique for future wireless communications to mitigate the spectrum scarcity issue. One of the most important challenge of a cognitive radio system is to identify the presence of primary (licensed) users over a wide range of frequency spectrum at a particular time and specific geographic location. In this paper, a spectrum sensing technique for cognitive radios based on discriminant analysis, called spectrum discriminator is studied. It is a blind detection technique where no prior knowledge about the measured signal is needed. In this paper, this spectrum sensing technique is extended to a cooperative environment using an adaptive cooperative spectrum sensing scheme based on the optimal data fusion rule. In the proposed method, secondary users efficiently cooperate to achieve superior detection accuracy with minimum cooperation overhead. The algorithm is able to detect the presence or absence of signals in any kind of spectrum. Hence, this method becomes a strong basis for a high quality operation mode of cognitive radios. Simulation results show that the proposed cooperative spectrum sensing scheme outperforms the conventional methods even under low SNR conditions.