Research On Low Energy Consumption And Cell-Free Massive MIMO System Deployment Assisted By RIS

With the development of mobile communication system and the arrival of the Internet of everything,users’ requirements for communication network speed increase rapidly,and the problems existing in the traditional cellular network architecture,such as interference between cells,handover and so on,become increasingly prominent.The cell free massive multiinput multioutput(MIMO)architecture put forward in the 6th generation mobile communication(6G)has attracted attention.Cell free massive MIMO system consists of a large number of access points(APs)connected to the CPU unit through backlink.These access points provide services to all users in the area under the same time-frequency resources,eliminating cell boundary restrictions,and effectively alleviating the problems existing in traditional cellular networks.However,with the increase of access points,reducing energy consumption becomes an urgent problem for cell free massive MIMO systems.Reconfigurable Intelligent Surface(RIS)has the characteristics of low cost and low energy consumption.By using a large number of passive components to change the phase and amplitude of the incident signal,RIS can enhance the useful signal and reduce the strength of the interference signal,while improving the performance of the system.It can also reduce system energy consumption.In this thesis,RIS assisted cell free massive MIMO system is studied from the perspective of improving system performance,which mainly includes the following aspects:Firstly,for the cell-free massive MIMO downlink system assisted by RIS,according to the position of the RIS,the access point and the user are divided into two categories.One is that the access point and the user are in the reflective region,and the other is in the non-reflective region.The user achievable rate and its approximate expression are derived,and the user sum rate maximization problem is proposed.Through the method of alternating optimization,the optimal position and phase shift of the RIS which can maximize the user sum rate are obtained.The simulation verifies the correctness of the approximate expression and the effectiveness of the proposed algorithm.In addition,it can be seen from the simulation results that the optimal position of the RIS is close to the user when the user is in a dense distribution.When the user is in a uniform distribution,the best position of the RIS is close to the center.On this basis,the number of access points required to achieve the same rate performance can be significantly reduced with the increase of the number of RIS elements,which can greatly reduce hardware and energy costs.Secondly,taking advantage of the flexible deployment of UAV,a cell-free massive MIMO system assisted by RIS carried by UAV is proposed.The RIS carried by UAV can reflect the signals of all ground access points and users,and the downlink user achievable rate and its approximate expression are derived.The optimal position of UAV and the optimal phase shift coefficient of RIS are obtained.The accuracy of the approximate expression and the effectiveness of the alternate optimization algorithm are verified by simulation.The results show that the UAV equipped with RIS can improve the system performance more significantly.Finally,after obtaining the optimal position of the UAV,the optimal flight trajectory and flight time from the initial point to the optimal position are designed for the UAV,so that the system and rate are always optimal during the flight of the UAV.