Study On Low Complexity Interference Alignment Solutions In Multi-cell MIMO Communication Systems

Future mobile communications face challenges in low latency,high data rates,and higher transmission quality.To address these challenges,Massive Multiple-Input MultipleOutput(MIMO),full duplex communication,orthogonal frequency division multiplexing and ultra-dense heterogeneous cellular networks are considered key technologies with great potential for future mobile communication systems.However,with MIMO communication systems,the interference problem will become more serious as the number of users increases.The interference can lead to reduced system communication capacity,so interference management is critical for future wireless communication systems.Among interference management technologies,interference alignment(IA)technology can effectively eliminate interference and is one of the most promising technologies in interference management.However,IA techniques still have many technical problems in future communication networks,especially in the low-complexity solving of interference alignment algorithms.For this reason,this thesis investigates the problem and focuses on the following key points:1.The inter-cell interference problem,the outer precoding matrix and filtering matrix solution is solved first.The thesis focuses on the low-complexity IA solution under the multicell multi-user MIMO interference alignment broadcast channel(IFBC)model.In the multicell multi-user IFBC model,each user is subject to inter-cell interference(ICI),i.e.,interference from other base stations.We first convert the multi-cell multi-user MIMO IFBC model into a multi-user interference channel(IC)model,and then solve the precoding matrix and filtering matrix of this multi-user IC model by the IA algorithm based on the alignment chain.And the IA algorithm based on the alignment chain is modified accordingly to derive the relationship between the number of transmitting and receiving antennas and the degrees of freedom(DOF).2.In the IFBC model,users are not only subject to ICI,but also to inter-user interference(IUI),and the inter precoding matrix and filtering matrix are designed for the mutual interference problem between users in the same cell.After the outer precoding matrix and the filtering matrix are solved,the system model changes from a multi-cell multi-user IFBC model to a multiple single-cell multi-user IFBC model.The channel matrix is changed by the action of the outer precoding matrix and the filtering matrix.The achievable DOF of this closed-form IA algorithm is derived and compared with other algorithms.The effectiveness of the algorithm is demonstrated by simulation verification.