Due to the individualistic nature of the femtocells and the uncertainty on the number and location of these devices, self-organization techniques play a very important role in successfully deploying and managing a large femtocell tier. This paper proposes a distributed power self-optimization scheme to suppress the interference and optimize the energy efficiency. First, the non-cooperative power self- optimization game is established, which is demonstrated to converge to a pure and unique Nash Equilibrium. Then, the impact of different power constraint conditions on the equilibrium is analyzed. Finally, a distributed power self- optimization algorithm is presented to achieve the equilibrium. With practical LTE parameters and 3GPP dual-strip femtocell model, simulation results show that the proposed scheme has fast and stable convergence and improves the energy efficiency significantly compared with Iterative Water Filling (IWF) algorithm. Furthermore, two power constraint conditions manifest different performance in terms of the energy efficiency.
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