Research On Pilot Contamination Suppression Methods In Cell-Free Massive MIMO System

In order to meet the surging demand of data traffic and solve the problems caused by the connection of massive terminal devices,massive multiple input multiple output(MIMO)technology with high channel spatial freedom has become a key technology of 5G and has been widely studied.The continuous division of cells in traditional cellular network architecture causes users at the edge of the cell to suffer more and more serious intercell interference and have poor service experience,thus cell free appears.The cell free technology changes from the base station-centric to the user-centric.By deploying a large number of access points(AP)around users to serve all users simultaneously,it not only eliminates the cell boundary and successfully solves the intercell interference problem,but also provides uniform service quality for all users.In the cell-free massive MIMO system,the limited time-frequency resources cause the number of users to be much larger than the number of available orthogonal pilots.When all users send pilot sequences to the access point at the same time during the uplink training phase,the same pilot sequence may be used by multiple users,resulting in pilot contamination.The existing research shows that the channel estimation error will be increased due to pilot contamination,and the accuracy of channel estimation will be decreased,which leads to the serious degradation of system performance.Therefore,the pilot contamination suppression methods for cell-free massive MIMO system are studied in this thesis.The main work and innovation of this thesis are as follows:From the perspective of the pilot assignment scheme to reduce the pilot contamination,this thesis proposes a pilot assignment method based on the location information equalization.In this method,the large-scale fading coefficient was used to determine the first user assigned pilot sequence,and the distance between the user and each user was calculated with the location service information as the center.Pilot sequence was assigned to all users in turn according to the principle from near to far,and the frequency of use of each pilot sequence was recorded to avoid the situation that a pilot sequence was underused or unused.Compared with the existing pilot assignment method,by considering the geographical location information of users,users far apart can use the same pilot more accurately,and at the same time,the frequency of each pilot is roughly the same.Simulation results show that this method can effectively reduce the channel estimation error and improve the spectral efficiency of the system.From the perspective of pilot transmitting power optimization,this thesis proposes a pilot power control algorithm combining K-means pilot assignment.Firstly,based on the K-means clustering algorithm,the centroid selection of each cluster is iteratively optimized according to the setting principle to obtain the optimal cluster scheme,and the orthogonal pilot sequence is allocated to the users in each cluster independently.Then,a maximum and minimum optimization problem is proposed which takes the maximum of the user pilot transmitting power as the constraint and the normalized mean square error as the objective function.Finally,continuous convex approximation is used to solve the non-convex optimization problem.The simulation results show that the optimization of pilot sequence transmission power can further reduce pilot contamination after pilot effective assignment,and significantly improve the average spectral efficiency of users.