Interference-Aware Spectrum Access Self-Organization: A Weighted Graph Game Perspective

We investigate the spectrum access problem in wireless canonical networks, where several network access points (NAPs) share some spectrum in a self-organization manner. A key feature enabling spectrum spatial reuse across nodes is the local interaction, that is, the interferences or direct influences only occur among neighboring nodes. Traditional works model the local interaction relationship by graphs, which, however, fails to characterize the diversity in the interference relationships and results in degradation in the spectrum utilization efficiency. In this paper, we incorporate the interference-awareness into spectrum access. Specifically, we extent the existing graph models to weighted graphs, where the degree of interference is explored and abstracted as the edge weight. On this basis, we formulate the spectrum access self-organization problem as a weighted graph game and analyze the existence and performance bounds of its Nash equilibriums. Finally, an interference-aware spectrum access algorithm achieving Nash equilibriums is proposed, where NAPs select channels according to the number of effectively interfering users instead of the number of interfering NAPs. Simulation results verified the superiority of the weighted graph game and the effectiveness of the spectrum access algorithm.