Capacity Maximization in Cognitive Networks: A Stackelberg Game-Theoretic Perspective

Abstract

Contrary to previous works, we focus on cooperation and competition relationship and the interactive dynamic behavior between multiple primary users (PUs) and secondary users (SUs) in a multiple cognitive interference channel context. Because of different levels of context information perceived by different types of players, e.g. the PUs and the SUs, and unbalanced nature of the spectrum priority among the multi-SUs/Pus in this setting, we investigate capacity maximization using the Stackelberg game modeling approach. Especially, we analyze the multi-leaders and multi-followers case, and further give a one-by-one case for making this model clear. Some conclusions are given via theorems. In addition, we propose the distributed iterative water-filling algorithms (IWFA) for pursuing Nash equilibrium solution (NES) and the Stackelberg equilibrium solution (SES) with low implementation complexity after analyzing and deriving the newly formulated game model in detail. Simulations results verify the performance of the proposed approaches in this paper.