Interference-Aware Energy-Efficient Resource Allocation for Heterogeneous Networks with Incomplete Channel State Information

In heterogeneous networks, interference management is very important since the interference due to spectrum-sharing can significantly decrease the overall performance. In the existing work, various resource allocation methods are proposed to either improve energy efficiency or alleviate interference. Very little research has addressed their joint interaction. Furthermore, most existing work assumes that all of the channel state information is known, which might not be realistic. In this paper, we propose a game-theoretical scheme using energy-efficient resource allocation and interference pricing for an interference-limited environment in two-tier heterogeneous networks without complete channel state information. We formulate the problems of resource allocation and interference management as a two-stage Stackelberg game with incomplete information. A backward induction method is used to analyze the proposed game, since it can capture the sequential dependencies of the decisions in the stages of the game.