Research On Uplink Pilot Assignment Scheme Of Cell-free Massive MIMO System

In recent years,the Cell-Free massive multiple input multiple output(MIMO)system has attracted much attention from both academia and industry due to its numerous advantages such as no inter-cell interference,large throughput,high spectral efficiency(SE),and low deployment cost.In the cellfree massive MIMO system,to obtain the channel state information(CSI)between the AP and the user,it is necessary to use pilots for channel estimation during the uplink training phase.However,in practical applications,the length of the pilot sequence is limited by the coherence interval,that is,the number of orthogonal pilots is limited,which is often much smaller than the number of users.Therefore,some users must reuse the same pilot sequence,which will interfere with channel estimation.This phenomenon is called pilot contamination.An effective way to suppress pilot contamination is to allocate pilots legitimately.Based on this,this paper studies the pilot assignment scheme of cell-free massive MIMO system.The main contributions of this thesis are summarized as follows:1)This thesis studies existing pilot assignment schemes,including random pilot assignment(RPA),greedy pilot assignment(GPA),location-based greedy pilot assignment(LBGPA),graph coloring(GC)based pilot assignment,and Hungarian algorithm(HA)based pilot assignment.The schemes are compared and analyzed from the aspects of algorithm implementation process,time complexity,and performance.2)To further suppress pilot contamination and improve the SE for users,all interference relationships among users are considered and AP selection algorithms and Ant Colony Optimization(ACO)are combined to allocate different pilots to adjacent users as much as possible.Then the pilot assignment based on ACO is proposed.The scheme aims to minimize the normalized mean square error(NMSE)of channel estimation and solves the sub-optimal solution of the pilot assignment problem.Simulation results show that the ACO-based pilot assignment scheme can significantly improve the SE for more than 95% of the users,reduce channel estimation errors,and effectively suppress pilot contamination.3)This thesis transforms the pilot assignment problem into a multidimensional discrete resource assignment problem and proposes a pilot allocation scheme based on Multidimensional Discrete Particle Swarm Optimization(MDPSO)to find a sub-optimal solution for the pilot assignment problem,with the objective of maximizing the total SE of the downlink users.Considering the convergence speed of MDPSO algorithm is closely related to the initial positions of particles,the Latin hypercube sampling(LHS)algorithm is adopted to assign values to the initial particles,ensuring not only the fairness of pilot assignment but also reducing the number of iterations required by the MDPSO algorithm.Simulation results show that the proposed pilot assignment scheme has a fast convergence speed.Compared with several typical pilot assignment schemes,the SE of the downlink users is significantly improved.