Research On Precoding Algorithm For Energy Efficiency Optimization In Massive MIMO Systems

With the advent of the 5G era,growing user demands pose a great challenge to current wireless communication technologies.The next generation wireless communication systems should further improve spectrum efficiency,and focus on the problem of energy efficiency.Massive MIMO can significantly improve the spectrum utilization of wireless communication systems by configuring large antenna arrays at the base station or user terminal,which is considered to be one of the key techniques in the next generation wireless communication systems.The precoding technology is the main interference suppression technology in the downlink of the Massive MIMO systems.Based on this background,we focus on the precoding technology for the Massive MIMO systems in this dissertation.The main research contents of this thesis are as follows:(1)We analyze the gain source,characteristics and typical application scenarios of the Massive MIMO systems,and discuss the channel modeling of MIMO systems in detail.For the fading characteristics of wireless channels,this thesis analyzes the statistical models of large-scale fading and small-scale fading.Based on the wireless transmission channel model,we derive the MIMO channel matrix and investigate the 2D channel model and 3D channel model of MIMO systems.(2)We investigate the energy efficiency optimization of the Massive MIMO systems.In order to further improve the energy efficiency of the systems,we introduce micro base station in the macro cell,construct the system model of multilayer heterogeneous network based on the Ultra-Dense Network.In this system model,we investigate the energy efficiency optimal precoding algorithm and resource allocation strategy.We use the user information rate as QoS constraints to guarantee the quality of user service and limit the transmission power of each base station,therefore,the optimization problem is formulated as a non-convex fractional programming problem.By converting the problem into semidefinite programming problem,we can use the interior point method to solve this problem.Then,we obtain the energy efficiency optimal precoding algorithm and the optimal resource allocation strategy in this system model.The simulation results show that the multilayer heterogeneous network model can significantly improve the energy efficiency of the Massive MIMO systems.(3)In the Massive MIMO systems with multilayer heterogeneous network topology,in order to reduce the complexity of the precoding algorithm,we propose an energy efficiency suboptimal precoding algorithm based on linear MMSE precding(EES-MMSE).We analyze the basic principle of linear precoding in the downlink of the multi-user MIMO systems,and introduce the concept of power control matrix in the precoding algorithm.Then,we discuss the difference between non-linear precoding and linear precoding,and the performance of linear MRT,ZF and MMSE precoding is analyzed and simulated.In the multi-layer heterogeneous Massive MIMO system model,the EES-MMSE precoding algorithm was proposed.The simulation results show that the time complexity of the EES-MMSE precoding algorithm is greatly reduced.The energy efficiency of EES-MMSE algorithm is close to the energy efficiency optimal precoding algorithm and superior to the linear MMSE precoding algorithm,the energy efficiency suboptimal precoding algorithm based on ZF precoding.