Demand responsive pricing competition of two MVNOs in dynamic spectrum access

In order to fully utilize the scarce wireless spectrum resources, many dynamic spectrum access approaches have emerged to enhance the spectrum efficiency in the spectrum market. From the economic point of view, in this paper we investigate the demand responsive pricing competition between two cognitive mobile virtual network operators (MVNOs) in a duopoly spectrum market and verify the pricing decisions as well as equilibrium. In addition, the secondary end user's heterogeneous preference over the rates that provided by the MVNOs is taken into account. Bertrand game theory is adopted to address the dynamic spectrum access problem. Through backward induction, a unique equilibrium as the solution of the game is obtained, which shows the stability of the spectrum market and the validity of the proposed approach.

[1]  Mihaela van der Schaar,et al.  Spectrum Access Games and Strategic Learning in Cognitive Radio Networks for Delay-Critical Applications , 2009, Proceedings of the IEEE.

[2]  J. Tirole The Theory of Industrial Organization , 1988 .

[3]  An He,et al.  A Survey of Artificial Intelligence for Cognitive Radios , 2010, IEEE Transactions on Vehicular Technology.

[4]  Christian M. Dippon,et al.  Voluntary relationships among mobile network operators and mobile virtual network operators: An economic explanation , 2009, Inf. Econ. Policy.

[5]  Brian M. Sadler,et al.  A Survey of Dynamic Spectrum Access , 2007, IEEE Signal Processing Magazine.

[6]  Alexander M. Wyglinski,et al.  An adaptive spectrum sensing architecture for dynamic spectrum access networks , 2009, IEEE Transactions on Wireless Communications.

[7]  J. Nash,et al.  NON-COOPERATIVE GAMES , 1951, Classics in Game Theory.

[8]  G. Bischi,et al.  Multistability in a dynamic Cournot game with three oligopolists , 1999, Mathematics and Computers in Simulation.

[9]  Simon Haykin,et al.  Cognitive radio: brain-empowered wireless communications , 2005, IEEE Journal on Selected Areas in Communications.

[10]  Venugopal V. Veeravalli,et al.  Algorithms for Dynamic Spectrum Access With Learning for Cognitive Radio , 2008, IEEE Transactions on Signal Processing.