Energy-efficient user association in cellular networks: A population game approach

In this paper, we address the problem of associating mobile stations with base stations (BSs) in an energy-efficient manner. We take the population game approach, which allows tractable analysis of many selfish mobiles without growing mathematical complexity, where our study provides two practical implications on energy-efficient BS associations: (i) how to control so-called association pricing so that an entire cellular network is operated with the goal of optimizing a social objective, and (ii) how to develop distributed, energy-efficient association algorithms. To that end, we first define a game, where mobile stations are the players, and their association portion for different base stations are their strategies. Then, from our equilibrium analysis, we prove that a simple power-dependent pricing by operators leads Nash equilibrium to be equal to the optimal solution of a social optimization problem (i.e., zero price-of-anarchy). Next, we study three evolution dynamics of mobile stations, each expressed as a differential equation, and connect each of them to a distributed association control mechanism, where three dynamics provably or experimentally converge to the Nash equilibrium (which is equal to the socially optimal point).