Research On Limited Feedback Scheme For Massive MIMO Systems

Massive MIMO is one of the hot techniques in the fifth generation(5G)wireless systems.The deployment of numerous antennas enables Massive MIMO systems to achieve not only higher system capacity,but also higher spectrum and energy efficiency than conventional MIMO systems.But at the same time,large number of antennas also leads to heavy feedback overhead.Therefore,it's of great significance to find a feedback scheme,which can lower the feedback overhead and also promise good system performance for Massive MIMO.This work was supported by the cooperation project "Network Architecture Evolution Strategy Research on Broadband Mobile Communication for the Future" between the Next Generation Communication System Theory and Technology Laboratory of BUPT and China Unicom Network Technology Research Institute.This thesis focused on the research of limited feedback and proposed a principal component analysis(PCA)based limited feedback scheme for Massive MIMO.Furthermore,Kalman filter was introduced to improve the performance of the proposed scheme,when channel estimation is non-ideal.First of all,this thesis gave a brief introduction to the concept,characteristics and major research directions of Massive MIMO.Based on this,a PCA based limited feedback scheme was proposed,also its feedback overhead,codebook search complexity and normalized upper boundary of performance loss was analyzed.Theoretical analysis and simulation results showed that the proposed scheme can achieve a tradeoff between system capacity and feedback overhead.Furtherly,this thesis introduced Kalman filter to the above proposed scheme to improve the system performance under non-ideal channel estimation circumstances.Simulation results confirmed that the system capacity was really improved after Kalman filter is introduced,due to its promotion on the accuracy of channel state information.