Research On Power Optimization Algorithm For Cell-Free Massive MIMO System

Looking back at the rapid development history of mobile communication systems in recent years,with the development of the 4th Generation Mobile Communication System(4G),people have ushered in the era of mobile Internet.While with the development of the 5th Generation Mobile Commumcation System(5G),peolpe have entered the era of the Internet of Things.Because of its high speed,low latency,and large connection,5G has been widely used in various scenarios such as industry,telemedicine,autonomous driving,smart home,and robotics.It has revolutionized the working modes of various industries and greatly changed people’s way of production and lifestyle.With the maturity,commercialization and popularization of 5G technology,scholars have already carried out researches on the 6th Generation Mobile Commumcation System(6G).The goal of designing a 6G system is to truly realize the interconnection of Everything.At present,a new Cell-Free architecture has been widely studied in the physical layer,which introduces the idea of ‘user-centered’.At the same time,the most advantageous massive Multiple Input Multiple Output(MIMO)technology in 5G is used.‘User-centric’ means that in a wireless communication network,there are a large number of Access Points(AP),which can be deployed flexibly with low cost,and can cooperate with each other to provide high-performance services for a small number of users.Cell-Free architecture refers to eliminating the concept of cell in traditional cellular mobile communication systems.This system uses a large number of randomly distributed APs to shorten the physical distance from users,which not only greatly reduces the path loss,but also suppresses the frequent handover and poor edge coverage problems.Since the Cell-Free massive MIMO is a technology newly proposed in recent years,it is still in the initial stage of exploration.The current research mainly focuses on pilot allocation,AP selection,channel estimation,precoding scheme design,receiver design and power optimization.According to the future development trend and my research,aiming to develop a green communication system with high-performance and low-cost,this thesis mainly studies the uplink and downlink power optimization schemes of Cell-Free massive MIMO system.The power optimization schemes can reduce interference between users and improves system performance under the limited power consumption by adjusting the transmit power of APs or users in line with the certain criteria.The main work and innovations of this thesis are as follows:For the downlink of Cell-Free massive MIMO system,this thesis studies the power optimization problem of downlink users’ sum-rate maximization based on local Partial Zero-Forcing(PZF)precoding,and proposes a new power optimization scheme.Due to the random distribution,small size,and limited transmit power of APs,the Quality of Service(QoS)obtained by different users is not uniform without optimizing transmit power.In this thesis,under the premise that the transmit power consumption does not increase,an AP power allocation scheme is designed to ensure uniform QoS for all users in the system.Taking Successive Convex Approximation(SCA)as the core idea,it iteratively solves the suboptimal power control coefficient with a faster convergence speed and maximize downlink users’ sum-rate.The simulation results show that using this scheme can make the downlink users’ sum-rate converge to the maximum roughly at the seventh iteration.Compared with the traditional fixed power allocation scheme using full power transmission,the downlink users’ sum-rate is significantly improved,and this improvement is more obvious with the increase of the number of APs and users.For the uplink of Cell-Free massive MIMO system,considering the degradation of system performance caused by an active eavesdropping jammer,this thesis studies an uplink receiver scheme and proposes a new solution to the problem of uplink users’ sum-rate maximization.In a Cell-Free massive MIMO system,APs and users are allowed to operate at low transmit power.So,the jammer unwilling to coordinate with legitimate users can easily interfere with the channel estimation during the pilot training phase,thereby reducing the accuracy of estimation.It will affect the performance of the receiver designed on the basis of the channel estimation,and further reduces the achievable transmission rates of users,which poses a serious threat to the entire Cell-Free massive MIMO system.In order to overcome the influence of the jammer,this thesis studies an uplink receiver scheme by combining users’ channel estimation and jammer’s channel estimation.Without increasing transmit power consumption,based on the idea of weighted Minimum Mean Square Error(w MMSE),a user power allocation scheme is studied to maximize uplink users’ sum-rate.The simulation results show that the receiver designed in combination with the jammer channel estimation can make up for the influence of jammer on the users’ channel estimation.Compared with the traditional fixed power allocation scheme using full power transmission,the uplink users’ sum-rate is significantly improved.With the increase of the number of APs,the interference caused by the jammer to the uplink users’ sum-rate with the fixed power allocation scheme is more obvious.However,by using the power allocation scheme proposed in this thesis,the influence of interference can be offset,so that the uplink users’ sum-rate can be similar to the users’ sum-rate obtained with a fixed power allocation scheme without interference.