Research on cross-layer interference alignment algorithm based on user grouping in heterogeneous networks

Compared with the traditional communication network, the fifth generation mobile communication network (5G) has a significant improvement in system capacity, delay, spectrum efficiency and energy cost. However, the 5G network is developing towards network diversification, broadband and intelligence. Its wireless communication network will be a combination of multiple types of networks, which means that there will be more types of interference in the communication system, which will lead to the rate of the communication system and other performance degradation. In order to effectively reduce interference and improve the performance of communication systems, this paper proposes a cross-layer interference alignment (IA) algorithm based on user grouping for multi-user multi-input multi-output (MIMO) 5G two-tier heterogeneous networks. In this paper, firstly, the group interference alignment algorithm suitable for single-layer multi-cell is extended to two-layer heterogeneous networks. Then, in order to improve the utilization of antennas and system performance, a new interference alignment (IA) algorithm is proposed, that is, pico-users (PUEs) are grouped to align cross-layer interference, so as to obtain the receiving beamforming matrix of PUEs. In this process, a two-stage transmitting beamforming matrix is designed for the macro base station (MBS) to eliminate macro inter-user interference and cross-layer interference. Among them, due to the reciprocity of the time division duplex system (TDD), the second-stage transmit beamforming matrix of the MBS is designed by a distributed method. Analysis and simulation results show that the proposed algorithm is superior to other traditional interference alignment methods in sum rate and antenna configuration.