| The 5th generation(5G)is facing enormous challenges as explosive growth of data led by the access of massive terminal devices with the rapid development of mobile communication.As a core technology in 5G,although the deployment of a large number of antennas in massive multiple-input multiple-output(MIMO)can significantly increase the system capacity,the hardware cost and power consumption are also increased.Antenna selection technology can reduce system costs by cutting down the number of radio frequency links while ensuring the system performance,which has become an important research direction in massive MIMO systems.In addition,the energy consumption problem is becoming increasingly serious.In order to achieve "green communication",energy efficiency has become a core indicator in performance analysis of 5G systems and the research on energy efficiency optimization for massive MIMO systems is also imminent.The main works of this thesis are as follows:First,the system and channel models of massive MIMO are summarized.The algorithm and computational complexity of several existing antenna selection techniques are analyzed.The energy efficiency model and related optimization theory of the massive MIMO system are discussed.Second,aiming at the problem of increased channel correlation and interference caused by dense antenna deployment in the massive MIMO system,an antenna selection algorithm based on K-means clustering is proposed,which groups antennas based on correlation and selects antennas with the goal of maximizing system capacity.Simulation results show that the proposed algorithm can approach the performance of the optimal antenna selection with low computational complexity and provides significant advantage under strong correlation channels.Third,to maximize the system energy efficiency with the maximum transmit power constraint,a joint optimization model of antenna selection,user scheduling,and power allocation in the multiuser massive MIMO downlink communication system is established.A bi-directional search algorithm is proposed to solve the antenna selection and user scheduling problems jointly.Fractional programming and Lagrange dual method are used to solve the power allocation problem.Simulation results show that the proposed algorithm can effectively reduce system power consumption and improve system energy efficiency.This thesis focuses on the antenna selection technology and energy efficiency optimization in the massive MIMO system,explores antenna selection algorithm with better spectral efficiency,and proposes a solution to the joint optimization problem of antenna selection,user scheduling,and power allocation to maximize energy efficiency.The research results of this thesis are of great significance to the design and performance optimization of the massive MIMO system. |
