A game-theoretic approach to load balancing in cellular radio networks

Game theory provides an adequate methodology for analyzing topics in communication systems that include trade-offs such as the subject of load balancing. As a means of balancing the load in the network, users are handed over from highly loaded cells to lower loaded neighbors increasing the capacity usage and the Quality of Service (QoS). The algorithm that calculates the amount of the load that each cell should decide either to accept or to offload might differ if the base stations are from distinct vendors, which in-turn may have an impact on the performance of the network. In this paper, we study the load balancing problem using a game-theoretic approach where, in the worst case, each cell decides independently on the amount of load that maximizes its payoff in an uncoordinated way and investigate whether the resulting Nash equilibrium would exhaust the gains achieved. Moreover, we alter the behavior of the players using the linear pricing technique to have a more desirable equilibrium. The simulation results for the Long Term Evolution (LTE) network have shown that the Nash equilibrium point can still provide a remarkable increase in the capacity when compared to a system without load balancing and has a slight degradation in performance with respect to the equilibrium achieved by linear pricing.