Optimizing fuzzy decision systems with the Jaya algorithm for enhanced data transfer in multi-hop CRNs

Effective data transfer is essential in Multi-Hop Cognitive Radio Networks (CRNs) due to changing channel conditions and dynamic spectrum availability. To address this, this research presents a Jaya Algorithm Optimized Fuzzy Decision System (FDS) for channel selection, channel allocation, and spectrum management. The fuzzy decision-making system adapts transmission parameters based on network conditions, while the Jaya algorithm optimizes the FDS parameters to improve decision accuracy. This combined approach aims to minimize hidden node interference, reduce channel switching, and enhance spectrum utilization. Simulation results using MATLAB show improvements in packet delivery ratio (PDR) and channel utilization, demonstrating that the proposed method can significantly improve throughput and reliability in Multi-Hop CRNs. The proposed JAYA-FDS model achieves approximately 10% improvement in throughput, 0.1% enhancement in packet delivery ratio (PDR), and nearly 50% improvement in soft handoff performance compared with the conventional GA-FDS approach.