With the explosive growth of indoor data traffic in forthcoming fifth generation cellular networks, it is imperative for mobile network operators to improve network coverage and capacity. Femtocells are widely… Click to show full abstract
With the explosive growth of indoor data traffic in forthcoming fifth generation cellular networks, it is imperative for mobile network operators to improve network coverage and capacity. Femtocells are widely recognized as a promising technology to address these demands. As femtocells are sold or loaned by a mobile network operator (MNO) to its residential or enterprise customers, MNOs usually employ refunding scheme to compensate the femtocell holders (FHs) providing indoor access to other subscribers by configuring the femtocell to operate in open or hybrid access mode. Due to the selfishness nature, competition between network operators as well as femtocell holders makes it challenging for operators to select appropriate FHs for trading access resources. This inspires us to develop an effective refunding framework, with aim to improve overall network resource utilization, through promoting FHs to make reasonable access permission for well-matched macro users. In this paper, we develop a two-stage auction–Stackelberg game (ASGF) framework for access permission in femtocell networks, where MNO and mobile virtual network operator lease access resources from multiple FHs. We first design an auction mechanism to determine the winner femtocell that fulfils the access request of macro users. We next formulate the access permission problem between the winner femtocell and operators as a Stackelberg game, and theoretically prove the existence of unique equilibrium. As a higher system payoff can be gained by improving individual players’ payoff in the game, each player can choose the best response to others’ action by implementing access permission, while avoiding solving a complicated optimization problem. Numerical results validate the effectiveness of our proposed ASGF based refunding framework and the overall network efficiency can be improved significantly.
               
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