Implementation and Performance Analysis of Cognitive Radio with Frequency Updating Algorithm on Software-defined Radio Platform

Abstract

Wireless communication is being used in all communication standards. However, with each passing day, the bandwidth scarcity has become a significant concern for the upcoming wireless technologies. In order to address this concern, various techniques based on artificial intelligence have been designed. The basic intelligent radio called cognitive radio has been devised. It works on the basic principle of spectrum sensing and detecting the free frequency for transmission of the secondary user, who is an unlicensed user. This work proposes an efficient technique that has been developed to design cognitive radio based on SDR platform. The frequency updating algorithm has been added for the performance assessment of the proposed technique. The analysis posits that for every 10dB rise in Gaussian Noise, the bit error rate of secondary transmitter and spectrum sensor, cause an increment of 19.59% and 29.39%, respectively. It has been found that spectrum sensor is more prone to noise and that the Gaussian noise degrades the performance of the system. Therefore, it is pertinent that the spectrum sensor should be programmed carefully. This analysis shows that the best range of spectrum sensor under Gaussian noise is 0 to 0.1dB and the bit error rate is within this specified range.