Development and Evaluation of an Interference Mitigation Decision Framework for Enhanced Quality of Service in White Space Networks

This study proposes solutions to mitigate Cross Network Interference (CNI) and improve Quality of Service (QoS) in White Space (WS) networks. It reviews literature on interference in shared frequency bands and investigates WS prediction using Geo-Location Spectrum Databases (GLSDs), finding that outdated data reduces accuracy. To address this, a framework verifying GLSD results with reactive spectrum sensing is proposed, enhancing WS prediction and discovery. The study extends GLSD techniques to general CNI mitigation using algorithms and Software Defined Radio (SDR) architectures, supporting efficient spectrum sharing. The proposed Interference Mitigation Decision Framework (IMDF) saves 70 % of bandwidth without interference, compared to 14 % with traditional methods. This research aims to improve bandwidth utilization and reduce interference in future wireless networks, despite potential interference with coexisting systems.