This paper investigates the application of game theory tools in the context of cognitive radio networks (CRN). Specifically, we propose a resource management strategy with the objective to maximize a defined utility function subject to minimize the mutual interference caused by secondary users (SUs) with protection for primary users (PUs). In fact, we formulate a utility function to reflect the needs of PUs by verifying the outage probability constraint, and the per-user capacity by satisfying the signal-to-noise and interference ratio (SNIR) constraint, as well as to limit interference to PUs. Furthermore, the existence of the Nash equilibrium of the proposed game is established, as well as its uniqueness under some sufficient conditions. Theoretical and simulation results based on a realistic network setting, and a comparison with a previously published resource management method are provided in this paper. The reported results demonstrate the efficiency of the proposed technique in terms of CRN deployment while maintaining quality-of-service (QoS) for the primary system.
This paper investigates the application of game theory tools in the context of cognitive radio networks (CRN). Specifically, we propose a resource management strategy with the objective to maximize a defined utility function subject to minimize the mutual interference caused by secondary users (SUs) with protection for primary users (PUs). In fact, we formulate a utility function to reflect the needs of PUs by verifying the outage probability constraint, and the per-user capacity by satisfying the signal-to-noise and interference ratio (SNIR) constraint, as well as to limit interference to PUs. Furthermore, the existence of the Nash equilibrium of the proposed game is established, as well as its uniqueness under some sufficient conditions. Theoretical and simulation results based on a realistic network setting, and a comparison with a previously published resource management methods will be provided in this paper. The reported results demonstrate the efficiency of the proposed technique in terms of CRN deployment while maintaining quality-of-service (QoS) for the primary system.
