Research On Performance Analysis And Transmission Technology Of Large-scale Antenna Systems Under Imperfect CSI

In order to meet the increasing demand of data flow and better quality of service,and ensure that users can use more stable and efficient transmission services,the fifth generation mobile communication system(5G)needs to be able to meet the new requirements in terms of spectrum efficiency,energy efficiency and other aspects.Massive multiple input multiple output(MIMO)system can greatly improve system capacity and energy efficiency by using a large number of antennas at the base station and is one of the key technologies of 5G.In this context,this paper carries on the related performance analysis and transmission technology research,mainly including the performance analysis of Massive MIMO systems under high mobility scenarios,pilot allocation methods in large-scale distributed antenna systems(DAS)and a robust detection algorithm for Massive MIMO systems using orthogonal frequency division multiplexing(OFDM)with timing estimation errorsFirst of all,this paper introduces the research background,analyzes the relevant research status at home and abroad,then briefly introduces the relevant background knowledge involved in this paper,leading to the research content of this paper.After that,in view of the difficulty of channel estimation and tracking and the performance degradation of the communication systems designed according to the low-speed environment caused by the rapid change of high-speed mobile communication channel.In this case,the performance of a Massive MIMO system with pilot-assisted repetition coding and spatial multiplexing is studied,by using repetition coding,the system can improve performance by using Doppler diversity provided by high-speed channel.With minimum mean square error(MMSE)channel estimation,an equivalent channel model and the corresponding system model are presented.Based on random matrix theory,asymptotic expressions of the normalized achievable sum rate of the linear receivers,such as the maximal ratio combining(MRC)receiver,MMSE receiver and MRC-like receiver,are derived.In addition,according to the symbol error rate of the MRC-like receiver,the maximum normalized Doppler diversity order and the minimum coding gain loss can be achieved when the repetition number and signal-to-noise ratio tend to infinity,and the corresponding conditions are derived.Based on the theoretical results,the impacts of different system configurations and channel parameters on the system performance are demonstrated.Then,this paper introduces a large-scale distributed antenna systems model with pilotcontamination.Based on the model,the pilot assignment algorithm is studied.Firstly,this paper introduces the constrained K means clustering algorithm which can control the number of samples in a cluster obtained by clustering and Kuhn-Munkras algorithm which is used to match the vertexes in bipartite graph.By using the constrained K means clustering algorithm to divide the users into different clusters,and using KM algorithm to match the users and pilots,this paper proposes a pilot allocation algorithm based on the constrained K means clustering algorithm.After that,by further analyzing the relevant conclusions of large-scale DAS system,a low complexity pilot assignment algorithm based on greedy principle is proposed.Then,the complexity of the two pilot allocation algorithms is analyzed,and the performance of the two algorithms is compared with that of the random pilot allocation algorithm by simulation,the effectiveness of the algorithm is verified by the simulation results.Finally,considering that in multi-user system,the time delay between the base station antenna and the user will be different due to the different geographical location of the user.When orthogonal frequency division multiplexing(OFDM)is used to combat fading,the timing estimation error in timing synchronization will cause the signal rotation.Based on the multi-user Massive MIMO-OFDM system model with timing estimation error,this paper proposes a robust symbol detection algorithm based on the K means clustering algorithm,the complexity of the algorithm is analyzed,and the effectiveness of the algorithm is verified through simulation.