Interference Coordination Technology In Heterogeneous Network Based On Large Scale Antenna Arrays

In recent years,5G communication system has already drawn more and more research inter-est.Compared to 4G,the most challenging problem of 5G is to achieve higher system throughput.In order to meet this demand,researchers have proposed Massive multiple-input multiple-output(MIMO)technology and small-cell heterogeneous network technology.Compared with Mas-sive MIMO technology,which uses multi-antenna array gain to improve spectrum efficiency,small-cell heterogeneous networks enhance the local coverage by deploying plenty of small cell stations,and finally achieve significant spectral efficiency improvement.However,the com-plex cross-tier and intra-tier interference in a heterogeneous network can severely restrict the performance of the system.Therefore,how to effectively suppress these interferences is a chal-lenging problem.This dissertation mainly focuses on the scene of Massive MIMO-enabled het-erogeneous networks,and proposes a series of heterogeneous network interference coordination schemes.The main research contents are summarized as follows:In this paper,we first study the interference coordination of heterogeneous network based on MIMO-precoding optimization.Small-cell heterogeneous networks and Massive MIMO are two promising technologies in 5G networks.However,how to effectively combine Massive MIMO and small-cell heterogeneous networks to make full use of their advantages for interference co-ordination in heterogeneous networks,is a very challenging problem.As such,in this paper,we employ Massive MIMO at the macro-cell base station(MBS)and small-cell base station(SBS)simultaneously,and establish a general two-layer heterogeneous network model.Through a de-tailed analysis of the interference signals,we propose a MIMO-precoding optimization scheme based on Zero-forcing precoding.The core essence of the scheme is to use the spatial freedom of Massive MIMO to sacrifice the local channel gain in exchange for interference cancellation on the interference channel.Mathematical derivation and numerical simulation show that the proposed scheme can effectively eliminate the cross-tier and intra-tier interference.Secondly,this paper studies the interference coordination in full-duplex heterogeneous net-works with Massive MIMO.Like Massive MIMO and small-cell heterogeneous networks,Full Duplex technology is also one of the key technologies used to improve spectrum efficiency in 5G networks.Although studies have shown that both Massive MIMO and Full Duplex technologies are feasible for heterogeneous network interference coordination,more comprehensive analysis of how to effectively combine the three key technologies for interference coordination is still absent.In this paper,we provide an interference coordination framework for a two-tier hetero-geneous network that consists of a massive-MIMO enabled MBS and a number of full-duplex SBSs.To suppress the interferences and maximize the throughput,the full-duplex mode of each SBS at the wireless backhaul link,which has a different impact on the interference pattern,should be carefully selected.To address this problem,we propose two centralized algorithms for mode selection.In particular,in order to effectively reduce the computational cost of the MBS,we have also proposed a distributed algorithm that allows each SBS to determine the choice of mode by its self.Finally,the numerical simulation shows that the three algorithms we proposed do improve the system performance effectively,and the three algorithms have their advantages in system performance and computational time.Finally,we study the user resource allocation in Massive MIMO-enabled heterogeneous networks based on load balancing.In heterogeneous networks,there are great differences in transmit power and coverage between base stations.As such,how to enable users to select the appropriate base station for association and how to properly coordinate the interference in heterogeneous networks to achieve optimal system performance is an important load balancing problem.For Massive MIMO,the power comsumption of the system increases significantly with the number of antennas.Therefore,in order to balance the energy efficiency of the system,the user load balancing problem in this case is really different from that of a traditional heteroge-neous network.In this paper,we consider a two-layer heterogeneous network equipped with Massive MIMO at the MBS,and study the strategy of user association and resource allocation in this scenario.In order to minimize the total system power comsumption while satisfying quality of service(QoS)guarantee of users,we model this user resource allocation problem as a combi-natorial optimization problem,but the existence of discrete variables makes the problem difficult to solve.Through a series of equivalence transformations and the introduction of ancillary vari-ables,we transformed the original problem into a more trackable form.Finally,we propose an approximate optimal algorithm based on the concave-convex procedure(CCCP),and numerical simulations prove the effectiveness of our proposed algorithm.