Satisfy instead of maximize: Improving operation efficiency in wireless communication networks.

Spectrum scarcity, combined with the tremendous increase of mobile users and their need for personalized services with different Quality of Service (QoS) requirements, fuel the necessity for the design of resource management approaches that ensure operation efficiency, flexibility and scalability. In this paper, we provide a novel theoretical framework to study several forms of efficient and stable system operation points, stemming from the concept of Satisfaction Equilibria, in the context of wireless communication networks. Considering a wireless communication environment under the presence of the Gaussian Interference Channel (GIC), a non-cooperative game among the users is studied, where the users aim in a selfish manner to meet their Quality of Service (QoS) prerequisite, in terms of data rate. We argue that instead of maximizing the QoS which is generally energy costly, better energy-efficiency is achieved by targeting satisfactory QoS levels only, thus obtaining Satisfaction Equilibria solutions. The sufficient and necessary conditions that lead to the Satisfaction Equilibrium are initially provided for the two-user case and the Efficient Satisfaction Equilibrium (ESE) is determined, where the users satisfy their QoS constraints with the lowest possible cost (i.e., power). An algorithmic approach following the best-response dynamics is provided to treat the multi-user case. To study and evaluate these equilibria operation points in a formal and quantitative manner, we coin some new theoretical concepts, namely the Price of Efficiency, Max Price of Efficiency and Max Price of Satisfaction, expressing the tradeoff of the achieved utility and the corresponding cost or the distance between the Satisfaction Equilibria of a given objective function. Finally, the performance evaluation of the proposed framework is obtained via modeling and simulation.