Distributed hierarchical game-based algorithm for downlink power allocation in OFDMA femtocell networks

Abstract

Femtocell is a promising technique for mobile operators to improve coverage and to provide high-data rate services in a cost-efficient manner. In this study, we investigate the problem of downlink power allocation in an orthogonal frequency division multiple access femtocell network. Femto-access points and macro-base stations in the network maximize their capacity and compete with each other through power allocation. This competition is captured in the framework of a Stackelberg game, and the Stackelberg equilibrium is introduced as the problem solution. We divide the strategy of MBSs into two substrategies (channel selection strategy and power strategy) to improve the performance of MBSs. The two substrategies interact with each other in the process of achieving Stackelberg equilibrium. The hierarchical iterative algorithm is proposed for MBSs and FAPs to achieve the maximum capacity game equilibrium in a distributed manner. A dynamic step size mechanism and a method that copes with variational player number are proposed to decrease the algorithm cost. Numerical results show that the performance of the proposed algorithm is better than the performances of other algorithms.