Research On Space-Time Interference Coordination In Heterogeneous Networks

With the rapid development of intelligent terminals and wireless application,wireless data demands grows exponentially.Improving wireless system throughput is key target for 5G system to deal with the growing users' demands for user rates.Heterogeneous networks(HetNets),comprised with macro base station and low power nodes,which reduces the distance between users and base station is a promising way to cover the traffic demands in hotspot zones.However,the HetNets are facing many challenges.In order to improve the system spectrum efficiency,Macro base stations and low power nodes are deployed with the same frequency band.The intercell interference is the bottleneck to improving system performance.Furthermore,the measures for load balancing exacerbates the interference for the edge users.Therefore,it needs effective interference coordination to improve the system performance.The thesis focus on interference coordination in downlink HetNets system and proposes a joint space-time interference coordination method to improve system performance.The base stations are deployed with the same frequency band in HetNets,which results in strong interference for edge users.The interference received by edge users is the bottleneck to improving system performance.To over this,as a widely used interference coordination method,almost blank subframes(ABS)can improve the service quality of edge users,but it will waste the precious time resource of macro base stations for it will mute on ABS.There is more effective interference coordination method in multi-antenna HetNets.In this thesis,we propose a joint time domain and coordination beamforming interference coordination method.We divide the frames into norm subframes(NS)and interference nulling subframs(INS).On NS,the central users are scheduled by base stations.On INS,the MBSs use zero-forcing beamforming to mitigate the interference for the edge users.In the meantime,the remaining degrees of freedom are used to serve the macro users.Then,we formulate a utility maximization problem based on proportional fairness,where user association and INS ratio are jointly optimized.The formulated problem is an NP-hard problem which is hard to solve directly.Then the problem is decomposed into two subproblems and an efficient joint user association and interference coordination scheme is proposed.Simulation results show that the proposed strategy can significantly improve the network utility and average throughput.Using coordination beamforming as an interference coordination method,users receive signal from single base station.To further improve quality of users' signal,the thesis then proposes joint time and partial joint transmission interference coordination method.Compared with coordination beamforming,joint transmission scheme needs to share channel state information(CSI)and user data information,which imposes higher requirements on the backhaul links and computing capabilities of the base station.Therefore,in this thesis,the interference coordination scheme only considers the cooperation between the macro base station and Pico base station and does not consider the joint transmission between the Pico base stations.We divide the frames into NS and joint transmission subframs(JTS).In NS,the base stations schedule the central users.In JTS,macro base stations and Pico base stations jointly send data to edge users.We jointly optimize JTS ratio and precoding vector to maximize weighted sum throughput.The formulated problem is not a convex optimization problem,which cannot be solved directly.Then the original problem is decomposed into two subproblems and an alternative algorithm is proposed to solve it efficiently.Numerical results show that the proposed scheme can achieve good performance over other schemes in terms of edge users' throughput and system throughput.