Nash Bargaining-Based Economic Analysis of Opportunistic Cognitive Cellular Networks

Abstract

We analyse a cognitive cellular network comprising of a primary and a secondary network operator (PNO and SNO). The SNO implements distributed detection to opportunistically access the licensed band. In return, the PNO requests the SNO to pay a remuneration. The PNO judiciously balances between the revenue gained from its subscribers and the payment earned from the SNO. On the other hand, the SNO must earn a positive utility to maintain its infrastructure. Consequently, a two-person non-cooperative bargaining game is formulated where the operators agree upon the value of the following factors: base station activity probabilites and the payment from the SNO. The PNO is aware of detection and false-alarm probabilities of spectrum sensing by the SNO and hence can infer how the interference created by missed detection degrades its capacity. We establish that our formulated game has a unique Nash solution. For linear demands, we derive an approximate closed-form solution. Numerical analysis reveals several insightful results. For example, we exhibit that, if the user number of the SNO lies below a certain threshold, the cognitive network appears to be economically unsustainable. We also show the functional dependence of the bargaining outcome on various system parameters.