HetNets Selection by Clients: Convergence, Efficiency, and Practicality
Abstract: We study the dynamics of network selection in heterogeneous wireless networks based on client-side side control. Clients in such networks selfishly select the best radio access technology (RAT) that maximizes their own throughputs. We study two general classes of throughput models that capture the basic properties of random access (e.g., Wi Wi-Fi) Fi) and scheduled access (e.g., WiMAX, LTE, and 3G) networks. Formulating the problem as a non non-cooperative cooperative game, we study its existence of equilibria, convergence time, efficiency, efficiency, and practicality. Our results reveal that: 1) single-class class RAT selection games converge to Nash equilibria, while an improvement path can be repeated infinitely with a mixture of classes; 2) we provide tight bounds on the convergence time of these games; games; 3) we analyze the Pareto-efficiency efficiency of the Nash equilibria of these games, deriving the conditions under which Nash equilibria are Pareto-optimal, Pareto optimal, and quantifying the distance of equilibria with respect to the set of Pareto-dominant Pareto dominant points when the cconditions are not satisfied; and 4) with extensive measurement-driven measurement driven simulations, we show that RAT selection games converge to Nash equilibria in a small number of steps, and are amenable to practical implementation. We also investigate the impact of noisyy throughput estimates, and propose solutions to handle them.