A mean-field game approach for distributed interference and resource management in heterogeneous cellular networks

Abstract

Intercell interference has been known as a crucial issue in heterogeneous networks where different transmitter-receiver pairs compete for system resources. We solve this problem in two steps. We firstly assign the macrocell user with the optimum number of subchannels, which just guarantee the required quality of service. Then, the remaining subchannels are left to be shared by a large number of small cells using mean field game theory, which is proved to be more tractable than conventional game theory. Using recent advances of mean field approximation techniques, we convert the entangled traditional game of small cells system into a mean-field game where resources allocation is much easier and simpler. With different network topologies, simulation results show the effectiveness of our proposed scheme.