Channel Estimate In Massive MIMO System In 5th-Generation

Today,requirements on high performance in Smartphone and wireless devices are getting more and more attention to improve high data transmission.This paper proposes research based on channel wireless mobile estimation by adopting the use of MIMO massive system deployment combined with 5 G mobile communication technology.To realize our approach,the paper describes first the concept of mobile channel estimation and gives the general evolution of massive MIMO in the 5 G generation.And finally,to achieve our research performance,the paper proposes a technique approach by adopting the Variational Bayesian algorithm implemented on MIMO MC-CDMA platform.The main simulation results show that the proposed variational Bayesian(VB)MIMO approach can perform the channel transmission with good reduction of peak to average power ratio(PAPR).The main contributions of the paper are summarized as below:To meet the new requirement of the wireless data transmission system,the multi-carrier code division multiple access(MC-CDMA)combined with variational Bayesian(VB)is proposed to improve the channel transmission capacity.This new algorithm can perform the lack observed in the implementation of tradition OFDM system which is mainly based on the EM algorithm in the case of significant uncertainty in the parameter estimation.In the use of Orthogonal Frequency Division Multiplexing(OFDM)systems during high-speed data transmission there is a high presence of peak-to-average ratio(PAPR)observed.to improve this problem,the paper introduces a called space-frequency block code(SFBC)model used for the complementary cumulative distribution function(CCDF).Therefore,the poor autocorrelation WH code has a steep descent gradient in the periodic interval,which reduces the difficulty of evaluating current MIMO performance.