Research On Channel Estimation And Precoding Technology Of 5G System Based On New Network Architecture

In recent years,with the further popularization of smart phones,users demand for high-speed data services was exploded,these needs to promote our fifth generation mobile communication system research.At present,China,the European Union and the United States have started the 5G system key technology research,and 5G system is expected to begin commercial in 2020.Compared to existing 4G systems,5G systems need to further improve system performance in terms of system capacity and spectrum utilization.Therefore,the 5G system needs to apply some more efficient technical means,such as Massive-MIMO technology,channel estimation technology,precoding technology and so on.Massive-MIMO system has a complex,large number of real-time data calculation,it will greatly increase the system data processing delay,but the future 5G system has a very important demand,that is,data processing ultra-low latency.ITU,IMT-2020 and other domestic and foreign 5G research institutions have proposed 5G end-to-end delay requirements,that is,the ideal end-to-end delay of 1ms,the typical end-to-end delay of 5-10 ms.In order to meet the needs of the future 5G system for very low latency,In the second chapter,we introduce the basic idea of the new Software-Defined Protocol(SDP)network architecture,and put forward the software-defined sector(SDS)mode under this SDP network architecture,and then simulate the computational complexity performance of the software-defined sector mode.Finally,we introduce the time-based pilot frame format based on the software-defined sector pattern,and then carry out the simulation analysis of the computational complexity.Massive-MIMO technology has the advantage of high spectral efficiency,good robustness and high transmission rate,so it will be one of the most promising technologies in the next generation cellular mobile communication system(5G).The acquisition of channel state information for mobile channels is a key issue in Massive-MIMO systems.In the third chapter,we first introduce four classical channel estimation algorithms in traditional MIMO systems and analyze their performance and shortcomings in MassiveMIMO systems.Next,we propose a new software-defined sector mode channel estimation algorithm,which is the SDS-MMSE channel estimation algorithm,and then the algorithm performance simulation and result analysis were carried out.The proposed SDS-MMSE channel estimation algorithm can obtain MSE performance near the ideal MMSE channel estimation without additional overhead.We also get the MSE analysis expression for the algorithm presented in this article,which will help us to further system design and performance estimates.In the Massive-MIMO system,the linear precoding technique can achieve the performance of the approximate channel capacity due to the progressive orthogonal channel characteristics.In the fourth chapter,we introduce three classical precoding algorithms in Massive-MIMO systems,and then analyze their performance and problems.Then we propose a preprogramming algorithm based on Symmetric Successive Over Relaxation(SSOR),which is the SDS-SSOR precoding algorithm,and then we simulate it and analyze the simulation results.The SDS-SSOR precoding algorithm proposed in this paper not only can greatly reduce the computational complexity,but also can achieve the best performance near traditional ZF precoding.At the same time,using the channel of the Massive-MIMO system to have the progressive orthogonal channel characteristics,we propose a simple method to calculate the optimal relaxation parameter in the SDSSSOR precoding algorithm.