分层异构网络中基于斯坦克尔伯格博弈的资源分配算法

分层异构网络中家庭基站与宏基站之间往往存在干扰，如何分配资源以获得高谱率和高容量、保证用户性能一直是研究的重点。为了解决这个问题，本文提出了一种异构蜂窝网络中基于斯坦克尔伯格博弈的家庭基站与宏基站联合资源分配算法，算法首先基于图论的分簇算法对家庭基站和宏用户进行分簇和信道分配，以减少家庭基站之间的同层干扰和家庭基站层与宏蜂窝网络的跨层干扰；然后建立了联合家庭基站发射功率以及宏用户接入选择的斯坦克尔伯格博弈，推导出达到纳什均衡时的家庭基站发射功率的表达式，并据此为宏用户选择合适的接入策略。仿真结果表明，该算法能够有效地提高宏用户的信干噪比（SINR），家庭用户的性能也得到改善。 

A algorithm of resource allocation based on stacklberg game in heterogeneous hierarchical wireless networks

Macro station and femtocells usually interfere with each other in heterogeneous hierarchical wireless networks. How to achieve high spectrum utility and high capcity, ensure user performance is the important point of research. To solve this problem, a joint macrocell and femtocell resource allocation algorithm based on stackelberg game in heterogeneous hierarchical wireless networks was proposed in this paper. At first, a clustering algorithm based on graph coloring was used to divide femtocells into several clusters and allocate channels for decreasing the co-tier interference among femtocells and the cross-tier interference between macrocell and femtocells. Then this paper put forward a scheme based on stackelberg game which combined femtocell transmitting power control with macro user access selection, and also derived the of FAPs’(femtocell access point) transmitting power when the game achieved a Nash Equilibrium(NE). According to the NE of FAPs, macro users chose the suitable base station to access. The simulation results show that the algorithm can effctively increase the SINR of macro users. The performance of femto users is improved as well.