Blockchain-Based Security Enhancement and Spectrum Sensing in Cognitive Radio Network

Abstract

In recent times, wireless communication systems have been considered by a fixed spectrum allocation policy, where administrative agencies provide wireless spectrum to licensees on a long-term basis for high geographical areas. Cognitive radio networks (CRN) will provide a large bandwidth to mobile users. However, CRN networks impose challenges due to security issues and spectrum management issues. Hence, in this paper, blockchain based security enhancement and spectrum sensing method is developed for managing the spectrum as well as identify the malicious user in the CRN. In the CRN, spectrum sensing is a fundamental requirement which affected by the malicious user. The malicious user is attacking the general signal detection of network and disturbs the accuracy of the system performance. The occurrence of a malicious user in CRN sends false sensing data which decreases the presentation of the system. Blockchain-based security and spectrum sensing is achieved in the CRN network which empowers the system performance. The blockchain-based method is utilized to identify the malicious user in the CRN by an Adaptive threshold spectrum energy detection algorithm. The proposed method is implemented in MATLAB and performance is evaluated by performance metrics such as the probability of detection, false alarm probability, sensing performance gain, total error probability, missed detection probability, number of selected sensing nodes, average network throughput, and energy efficiency. The proposed method is compared by existing methods such as Friend or Foe and Tidal Trust Algorithm.