Spectrum Bargaining: A Model for Competitive Sharing of Unlicensed Radio Spectrum

Abstract

In this paper, we address the problem of dynamic channel access by a set of cognitive radio-enabled nodes, where each node acting in a selfish manner tries to access and use as many channels as possible, subject to interference constraints. We model the dynamic channel access problem as a modified Rubinstein–Stahl bargaining game. In our model, each node (player) negotiates with the other nodes in the network reduce in a distributed manner to obtain an agreeable sharing rule of the available channels such that no two interfering nodes use the same channel. We solve the bargaining game by finding subgame perfect Nash equilibrium (SPNE) strategies of the game. First, we consider finite horizon version of the bargaining game and investigate its SPNE strategies, which allow each node to maximize its utility against the other nodes (opponents). We then extend these results to the infinite horizon bargaining game. Furthermore, we identify Pareto optimal equilibria of the game, which help enhance network throughput. We conduct simulations to study how the “self-gain” maximizing strategy of the players impact systemwide performance.