A Dynamic Framework for Optimizing Spectrum Utilization and Interference Mitigation in White Space Networks - Ntuli, Elesa; Du Chunling; Moshe Timothy Masonta (The Indonesian Journal of Computer Science, 2025)
This study presents a framework for optimizing spectrum utilization and reducing interference in White Space (WS) networks using the Interference Mitigation Decision Framework (IMDF). The IMDF combines Geo-Location Spectrum Databases (GLSDs), reactive spectrum sensing, and Software Defined Radios (SDRs) to address the limitations of traditional spectrum allocation methods. The IMDF enhances allocation, reduces interference, and improves network performance by monitoring real-time spectrum usage. Simulations comparing IMDF with traditional GLSD-based methods show a 70% bandwidth saving, compared to 40% in traditional approaches. Additionally, IMDF reduces interference events by 30%, improving Quality of Service (QoS) and mitigating Cross Network Interference (CNI). With dynamic spectrum management, IMDF achieves 70% spectrum utilization, while traditional systems only reach 40%. These results demonstrate IMDF's effectiveness in dynamic environments, offering a robust solution for wireless service demand and interference mitigation in increasingly WS networks. The IMDF’s adaptability, combined with its efficient resource management, makes it a promising framework for the future of spectrum allocation in increasingly congested network environments.