Physical Interference Driven Dynamic Spectrum Management

Abstract

Dynamic spectrum management can drastically improve the performance of wireless networks struggling under increasing user demands. However, performing efficient spectrum allocation is a complex and difficult process. Current proposals make the problem tractable by simplifying interference constraints as conflict graphs, but they face potential performance degradation from inaccurate interference estimation. In this paper, we show that conflict graphs, if optimized properly, can produce spectrum allocations that closely match those derived from the physical interference model. Thus we propose PLAN, a systematic framework to produce conflict graphs based on physical interference characteristics. PLAN first applies an analytical framework to derive the criterion for identifying conflicting neighbors, capturing the cumulative effect of interference. PLAN then applies a local conflict adjustment algorithm to address heterogeneous interference conditions and improve spectrum allocation efficiency. Through detailed analysis and experimental evaluations, we show that PLAN builds a conflict graph to effectively represent the complex interference conditions and allow the reuse of efficient graph-based spectrum allocation solutions. PLAN also significantly outperforms the conventional graph model based solutions.