Cooperative Spectrum Sensing with Weighted Clustered Architecture

Wireless communication systems are built based on the transmission of electromagnetic waves (or radio waves) with frequencies in the range of 3 Hz to 300 GHz. today?s wireless networks are characterized by a static spectrum assignment policy. Recently, due to the increase in spectrum demand, however, this policy is faced with the spectrum scarcity at particular spectrum bands. On the contrary, a large portion of the assigned spectrum is still used sporadically leading to under-utilization of the significant amount of spectrum. The anticipated explosion of wireless applications creates an ever-increasing demand for radio spectrum. Unfortunately, spectrum is a finite resource. Because of the tremendous societal value of the finite spectrum, its use is carefully managed at the national and international level. Cognitive radio technology is proposed to solve these current spectrum inefficiency problems we propose weighted clustering strategy in which weightings are used to weight the cluster-decisions before combining. and compared it with the k-means clustering scheme in by simulation. The simulation results show that our proposed method improve the probability of detection and reduce the probability of error.