Enhancement of Cognitive Radio Spectrum with Proposed Cascade Filter Model

Abstract

The use of the frequency spectrum has become an urgent necessity, especially in the advanced generations of communications and various types of transmitted data. The radio spectrum is not being exploited effectively, primarily due to the current strict frequency allocation scheme. Only few bands of the spectrum are heavily utilized, such as those used for wireless base stations. Many bands are either not used at all or are only used infrequently. This problem has been solved through cognitive radio (CR) technology. CR technology faces many challenges in finding the unused frequency spectrum, especially the presence of noise in the spectrum analysis. This paper proposes a filter model with two-stages to enhance the cognitive radio performance and perform a comparison between proposed filter with the traditional cognitive radio techniques, by the means of QPSK modulation. The comparison result based on parameters such as the probability of detection as well as the probability of failure and the cumulative error rates. High probability of detection is required to achieve better network performance. A proposed filter model in the CR method has successfully passed all tests and provided better performance than other filters.