Game theoretical method for sum-rate maximization in full-duplex Massive MIMO Heterogeneous Networks

•We modeled a two-layer HetNets with Massive MIMO applied. The system works in full-duplex mode. Even full-duplex leads a huge interference, it is a more efficient system.•The game theoretical method is chosen to decline the effect of interference. A game was built base on this scenario.•By applying the game theoretical method, the maximum system sum rate is reached. In the experiment game theoretical method indeed perform better (higher sum rate) than random access method. It performed a better access scheduling in a dynamic system.•It turns out that users׳ power constraint (UL transmission and DL receiving constraints) is the major factor which limits system׳s performance. And compared to non-optimized model, game theoretical method has a better antiinterference ability.

In this paper, we consider Massive MIMO in two-layer Heterogeneous Networks. The system has a large self-interference and co-channel interference due to operation in full-duplex mode. By using Game Theory, an optimized sum-rate is achieved. We investigate the potential sum-rate before and after the optimization under the power constraints. It is shown that the game theoretical method performed a very good access scheduling. Compared to non-optimized model, game theoretical method can achieve higher sum-rate.