A Game-Theoretical Analysis of Wireless Markets Using Network Aggregation

Modeling wireless access and spectrum markets is challenging due to a plethora of technological and economic aspects that affect their performance. This work develops a modeling framework for analysing such markets using network economics, game theory, and queueing networks. The framework models the service selection of users as well as the competition and coalition among providers. It also develops tools and algorithms to analytically compute the Nash equilibriums (NEs) under the presence of discontinuities in the derivatives of the utility functions of providers. The analysis of different market scenarios reveals various interesting trends in the offered prices, market share, and revenue of providers depending on the user utility function, traffic demand, and mobility pattern. It also demonstrates the role of the quality of service (QoS) in the user utility function in reducing the intensity of competition and allowing for higher prices and revenue. However, the analysis of large-scale markets exhibits a high computational complexity. To improve the computational efficiency, we developed a network aggregation methodology based on the theorem of Norton. This aggregation allows the construction of equivalent networks for a specific region of interest, omitting the details of the entire networks. We demonstrate the aggregation algorithm in the context of capacity planning.