Power Control Of Cell-free Massive MIMO System

With the rapid development of information technology and its related industries,the current era has put forward higher requirements for the diversity of information services and communication performance,which requires more innovation of mobile communication technology.In the 1G to5 G mobile communication network system,with the use of cellular network structure,users need to switch cell frequently when moving in the system.Especially in the case of high rate requirements,the contradiction between coverage area and communication rate in the traditional cellular network framework becomes more and more prominent.Higher service throughput and delay requirements cannot be further met.Compared to current cellular networks,Cell-free Massive MIMO introduces the idea of "user-centric",eliminates the concept of Cell,and provides high signal gain and channel hardening characteristics,It provides an efficient communication framework for the further development of mobile communication.This thesis mainly studies the power control problem in the Cell-free Massive MIMO system,and proposes power optimization schemes for the power control problems in Max-SE,Max-Min and Max-EE respectively.For max-SE problem,which aims to maximize the overall spectral efficiency of the system,a fixed-point iterative optimization scheme is proposed in this thesis.By adding relaxation variables,the algorithm can solve the iterative expression of each variable in the uplink and downlink data transmission stage of the system respectively.The disadvantage of continuous convex approximation(SCA)algorithm that every iteration needs to solve the convex optimization problem is avoided,and the efficiency of solving is improved.In this thesis,the effectiveness of the proposed optimization scheme is verified by numerical simulation.The results show that the proposed scheme can significantly improve the total spectral efficiency of the system under the premise of meeting the transmission power limit and quality of service requirements,and has a faster computing speed compared with SCA algorithm.For max-min problem,the purpose is to maximize the minimum spectral efficiency in the system to maximize the service fairness of the system.In this thesis,an optimization model of the problem is derived,and a power optimization scheme based on accelerated proximal gradient algorithm(APG)is proposed,which smooths the original power control problem and then derives the iterative expression of each variable.Simulation results show that the optimized scheme can significantly increase the fairness of the system service,reducing the communication rate difference between the user,and is verified by comparing the optimized scheme can almost without sacrificing the overall spectral efficiency of the system,and proved to Cell-free Massive MIMO network can for each user to provide a unified communication service quality.For max-EE problems,the goal is to maximize the overall energy efficiency of the system.In this thesis,the energy efficiency model of the system is derived,and according to its special fractional structure,a nested decoupled optimization scheme is proposed,which can also solve the iterative closed expression of each variable,avoiding the call of convex optimization solver in each iteration step.Through numerical simulation,it is verified that the optimization scheme can significantly improve the overall energy efficiency of the system,and can provide a reference for access point selection.