Personalized Pricing for Efficient User-Centric Multi-Resource Control in 5G Wireless Networks

In this paper an analytical framework for the joint allocation of multiple physical resources under a dynamic personalized pricing setting, in a NOMA wireless network, is designed. Under our proposed user-centric paradigm, price is treated as a resource itself rather than simply being a control parameter and represents the user willingness to pay towards obtaining certain QoS levels. Each user expresses her satisfaction with respect to her and other users choices through a specifically designed utility function based on her unique characteristics and preferences. The resource allocation problem under consideration, becomes a distributed utility maximization problem, where each user updates her controllable parameters in an autonomous manner targeting at her satisfaction maximization. The problem is modeled and solved as a multivariable non cooperative game, admitting a unique Nash Equilibrium (NE), whose convergence is reached via a distributed and low complexity algorithm. Detailed numerical results, clearly demonstrate that the proposed framework allows the users to better exploit the system's resources, and therefore improve their overall satisfaction, while achieving significant improvements in the system operation in terms of power savings and achievable data rate.