Distributed power self-optimization with convex pricing in dense femtocell networks via an exact potential game

With the sharp increasing demand of the indoor coverage and network capacity, dense femtocells are the ultimate target of the femto cellular network deployment in urban environment However, dense femtocell deployment could introduce excessive inter-femtocell interference (IFI). To address this problem, this paper proposes a distributed power self-optimization scheme for the downlink of dense femtocell networks. First, a non-cooperative power self-optimization game framework is established based on the exact potential game, which is demonstrated to converge to a pure and unique Nash Equilibrium. Then, a novel convex pricing mechanism is presented to price the transmit power of femtocells. Finally, combined with Firefly Intelligence Optimization (FIO), an effective power self-optimization algorithm with guaranteed convergence is proposed to achieve the Nash Equilibrium. With practical LTE parameters and 3GPP dual-strip femtocell model, simulation results show that the proposed scheme dramatically reduce femtocells transmit power while improving the throughput of dense femtocell networks compared to the scheme with non-linear pricing.