Joint Optimization Of Pilot And Data Transmission In Massive MIMO Systems

With the rapid development of mobile Internet technology,mobile communication systems are increasingly demanding resource utilization and communication quality.Large-scale multi-input multi-output(MIMO)technology has the characteristics of effectively improving spectrum resource utilization and increasing system capacity,and is used as a key technology of 5G.However,in the traditional Time Division Duplexing(TDD)based transmission mode,the same set of orthogonal pilot sequences are used in each cell,which can reduce the spectrum resources occupied by the uplink pilot sequence,but will lead to pilot pollution when channel estimation is conducted between cells based on the same pilot frequency.This pilot pollution reduces the accuracy of channel estimation,which affects the performance of Massive MIMO systems.Therefore,it is very important to improve pilot pollution in Massive MIMO system based on TDD.In this paper,based on the summary of the basic principles of Massive MIMO technology,and the research status of channel estimation and pilot allocation scheme based on TDD,a dynamic pilot and data power allocation scheme is designed by using the channel state information estimated by Kalman filter instead of statistical representation,and combining with time channel correlation.In addition,a joint optimization scheme for transmission power and pilot allocation in TDD Massive MIMO system is proposed according to the correlation of time channel and the method of maximizing the minimum rate.The main work is summarized as follows:Firstly,a joint dynamic pilot and data power allocation scheme for TDD Massive MIMO systems is proposed.The scheme uses a Gauss-Markov process of timedependent channel to model the channel and combines with the Kalman filter to implement channel estimation,which enables the prior estimate to obtain a better channel preview before estimation.Based on the priori estimates generated during filtering,a deterministic approximation of the user rate in the next time slot can be derived,which can beused as a function of the prior channel estimates and a priori estimation errors of the relevant users with strong interference.Based on this priori estimate,it is possible to develop and resolve the rate allocation of the system prior to transmitting the pilot to maximize the minimum rate,thereby improving the effects of pilot pollution.Secondly,based on the scheme of pilot power allocation mentioned above,a joint optimization scheme for transmission power and pilot allocation in TDD Massive MIMO systems is proposed.Considering the trade-off between performance and complexity,this paper uses the deterministic approximation of the data rate in the first time slot and derives it as a function of the statistical value.In order to maximize the minimum rate of the system and iteratively optimize the transmission power and pilot allocation,the pilot power and data power are derived by successive approximation and relaxation variables in this paper.The pilot allocation scheme is adjusted based on the ratio of channel gain to suppression,thereby further reducing pilot pollution.According to the simulation results,the joint dynamic pilot and data power allocation scheme based on TDD Massive MIMO system can significantly reveal the dynamics of channel power and adaptively mitigate pilot pollution and balance mutual interference.In addition,under the joint optimization scheme of transmission power and pilot allocation,the minimum rate of the system is significantly higher than that of the traditional random allocation pilot scheme.This result confirms that the optimization scheme effectively improves the system performance,and lay a foundation for further research on optimizing the performance of Massive MIMO system through dynamic data transmission and pilot assignment.