Research On Key Techniques Of Interference Management In Massive MIMO Heterogeneous Network

Massive MIMO technology and heterogeneous networking technology will become the core technologies for the next generation of mobile communication system,which can effectively solve the user’s demand for high speed and mass access of mobile communication.Therefore,heterogeneous cellular network based on large-scale MIMO will become the network architecture model of next-generation mobile communication.While bringing significant performance improvements,the adoption of new technologies has also had some negative impacts,with the increase of interference in the network particularly prominent.Heterogeneous network makes the network structure from the traditional single-layer network into a multi-layer network,users receive interference signals not only from other users in the same layer,but also from users of other layers,how to effectively manage interference has become one of the current research hot spots.Interference alignment Improves the system transmission rate by aligning interfering signals into a same sub-space at the receiving end.Compared with the traditional interference cancellation strategies,it has significant advantages in performance and has been widely studied in recent years.Based on the interference alignment technology and combined with antenna selection and power allocation,this thesis focuses on the interference management of Massive MIMO heterogeneous cellular network scenarios,details as follows:Firstly,the principles of antenna selection,power allocation and interference alignment are introduced and analyzed,including the antenna selection algorithms and power allocation algorithms,the mathematical principle of interference alignment and the feasibility condition of interference alignment.Then,from the view of maximizing the system capacity,the interference alignment algorithm combined with the antenna selection technique is studied for Massive MIMO heterogeneous cellular networks.Traditional algorithms treat antenna selection and interference alignment as two separate steps,so the optimal solution cannot be obtained in most instances.This thesis first proposes a joint optimization algorithm that optimizes antenna selection and interference alignment as an entirety.In order to reduce the complexity of this algorithm,antenna selection is improved based on greedy strategy.For linear interference alignment,performance has been further enhanced by optimizes the pre-coding matrix.For distributed iterative interference alignment,in order to reduce the complexity of iterative computation,this thesis improves the proposed algorithm based on the idea of partial iteration,which further reduces the complexity of algorithm.Last,from the perspective of the minimum system error rate,the interference alignment algorithm combined with dynamic power allocation techniques is studied for Massive MIMO heterogeneous cellular networks.On the one hand,considering the dynamic power coordination problem between base stations,the traditional algorithms are not suitable for this scenario due to the significant differences in the transmission power of different types of base stations in heterogeneous cellular networks.In this thesis,the traditional algorithm is improved based on the secondary power coordination under the premise of retaining the performance gain of the original algorithm,it is applicable to heterogeneous networks.On the other hand,considering the power allocation algorithm between different data streams in the MIMO system,the BER performance of the system is further improved through the fairness-based power allocation strategy.Then,a twolayer power allocation scheme is proposed,and the interference alignment pre-coding matrices are optimized based on the matrix chord distance to further improve the system performance.