Adaptive Spectrum Monitoring Algorithm for Cognitive Radio Systems

Abstract

At present, the communications industry is one of the fastest-growing sectors, as well as an important component of modern society, which has led to rapid growth in demand for the radio frequency spectrum (RF). Since virtually all RF is distributed among corporations providing various communication services, it is becoming increasingly difficult to introduce new communication systems and technologies. The deficit of RF has led to the development of new communication systems aimed at the efficient use of radio frequency resources. These include the Cognitive Radio System (CRS), which makes it possible to use the RF of the primary user efficiently and without reducing the quality of service for all subscribers. In the previous article, we proposed an algorithm for implementing CRS based on models of spectral occupancy. One stage of the algorithm is spectrum monitoring. Spectrum monitoring is used to obtain actual information about the spectrum occupation. There are many scientific works aimed at detecting the signals of primary users. Due to its implementation simplicity and low complexity, the main method of signal detection is the use of an energy detector, which was implemented in our previous article. However, this approach is sensitive to various types of interference and fluctuations signal-to-noise ratio (SNR), due to the dynamics of the radio environment. A new detection algorithm using an adaptive threshold is therefore proposed. The value of the adaptive threshold is selected taking into account the noise power fluctuations, thus avoiding the disadvantages of the classical energy detector. Simulation results show that an adaptive threshold algorithm is more resistant to the dynamic changes of SNR than a classical algorithm. The new algorithm also makes it possible to increase the performance of the algorithm proposed by us for the implementation of CRS based on models of spectral occupancy.