Research On Green Self-Optimization Technologies Of Two-Tire Femtocell Networks

In two-tier femtocell networks, it’s crucial to mitigate the significant cross-tier interference and co-tier interference before femtocells widespread deployment. Besides, to reduce the energy consumption in communication networks, it’s very necessary to control the downlink transmit power of the femtocells. Ensure and improve the network performance through a smaller femtocell’s transmit power and make the concept of green communication come true. For that reason, in this paper, based on the SON characteristic of femtocell networks, we have studied the green self-optimization technologies of two-tier femtocell networks, where macrocell and femtocells share the same frequency.Firstly, the distributed optimization technology for energy efficiency maximation is proposed. Based on the SON characteristic of the femtocell, non-cooperative game is used to model the interaction among femtocells and a non-cooperative power self-optimization game converging to a pure and unique Nash Equilibrium is proposed. Combined with firefly intelligent optimization, a distributed power self-optimization algorithm is proposed to achieve the equilibrium. Simulation results show that the proposed technology can control the interference and optimization the energy efficiency more efficiently.Secondly, a kind of green self-optimization technologies is proposed based on potential game, which can be well used in dense femtocell networks. In this technology, to mitigate the significant co-tier interference in dense femtocell networks more efficiently, a convex pricing mechanism for femtocells is proposed and the performance optimization is constructed. This technology is modeled as a power self-optimization game via potential game, which is demonstrated to converge to a pure and unique Nash Equilibrium. Besides, an iteration algorithm is presented for the proposed game to converge to the Nash Equilibrium. With practical LTE parameters and a3GPP dual-strip femtocell model, the optimal parameter values are obtained through several simulations. Simulation results also show that the proposed game with convex pricing mechanism increases the femtocell network throughput by7%and reduces the average transmit power of femtocells by50%in dense femtocell networks, with respect to the compared schemes.