An Analytical Model for Dynamic Spectrum Sensing in Cognitive Radio Networks Using Blockchain Management
Nikhil Kumar Marriwala, Sunita Panda, Chandran Kamalanathan, N Sadhasivam, Vootla Subba Ramaiah · 2024
Recent advancements in wireless communication technology have brought about the pressing issue of increasing spectrum scarcity. This challenge in spectrum allocation arises from ongoing research in the field of wireless communication. Unfortunately, a significant portion of the spectrum remains underutilized within wireless networks. Cognitive radio (CR) presents an innovative solution to this problem by enabling unlicensed secondary users to coexist with licensed primary users within allocated spectrum bands without causing interference to the primary users’ communications. This paper promises to address the spectrum redundancy challenges and substantially improve the spectrum utilization efficiency. Cognitive radio networks (CRNs), alternatively known as dynamic spectrum access networks, are comprised of multiple CR nodes and are frequently referred to as next generation (XG) communication networks. These XG communication networks are expected to offer high-speed data transmission capabilities to adaptable users through a variety of wireless architectures and dynamic access protocols. Since CRNs share similarities with traditional wireless networks but operate in an external wireless medium, they are more susceptible to various types of attacks compared to their wired counterparts. This vulnerability stems from the fact that wireless media can be intercepted or exploited, potentially leading to channel congestion or data interception. This paper presents two key approaches: the node evaluation and selection (NES) algorithm and the secure spectrum sensing mechanism, which incorporate the user’s interaction history and connection distance, that are recorded in a public ledger and managed by a blockchain management system. The proposed algorithm facilitates the central aggregation point for selecting nodes with outstanding performance for cooperative sensing, thus enhancing the network’s security against malicious node attacks.