In this paper, we consider a dynamic scenario in which mobile users with elastic traffic arrive at a wireless heterogeneous system according to a Poisson arrival process. The wireless system consists of a set of overlapping network cells of different technologies. The protocols associated to each cell specify the throughput allocated to each user, given the cell load (i.e. the number of active users and their geographical positions). Meanwhile, mobile users (the players) can choose which cell to associate to. Suppose they collaborate to obtain an efficient and fair share of the global throughput. Then, two families of mechanisms can be considered: (i) either the users bargain at each stage of the system so as to obtain, given the present population, a fair share of the present throughput (repeated single-stage games), or (ii) users bargain so as to obtain a fair expected throughput during the total duration of their call (single stochastic game), taking into account the knowledge of the global (stochastic) arrival process and connection size. In this paper, we numerically compare the two policies and their resulting performance: does forecasting the future significantly impact the optimal mobile-to-cell association?