Research On Pilot Allocation Algorithm In Massive MIMO System

With the emergence of new application scenarios for wireless communication,there is an increasing demand for data transmission rates and high spectral efficiency in mobile communication systems.Massive MIMO technology can increase the transmission rate,spectrum efficiency and energy efficiency of mobile communication systems by using spatial freedom to configure a large number of antennas on the base station side of the cellular network.In Massive MIMO system,due to the limited pilot resources,the problem of pilot pollution caused by multiplexing the same pilot between neighboring cell users has become one of the bottlenecks restricting the performance of Massive MIMO systems.The topic of this thesis comes from the enterprise scientific research cooperation project "Research on the Key Technology and Business Analysis Technology of the New Generation Network".The thesis focuses on the pilot allocation algorithm in Massive MIMO systems,studies the pilot allocation problem of homogeneous cellular networks and heterogeneous cellular networks,and proposes clustering based pilot allocation algorithm(CPA)and greedy matching based pilot allocation algorithm(GMPA).The main work of the thesis is as follows:1)This thesis reviews the current research status of pilot contamination suppression of Massive MIMO systems.Firstly,the advantages and key problems of Massive MIMO technology are given;The pilot contamination problem affecting the advantages of Massive MIMO technology is analyzed and the direction and challenge of pilot contamination suppression technology are summarized;The research status and problem analysis of the pilot allocation technology studied in this thesis are carried out.2)Aiming at the problem of excessive pilot overhead in the existing pilot allocation scheme,this thesis proposes a clustering based pilot allocation algorithm.The proposed algorithm groups the users into low ICI(Inter-Cell Interference)group and high ICI group by defining user interference intensity related to large-scale fading information,users in low ICI group use orthogonal pilot sequences.Users in high ICI group use clustering algorithm to cluster according to their location,according to the clustering results,users are divided into two categories:users in the same cell user clusters are allocated orthogonal pilot sequences for each other,users in the different cell user clusters are guaranteed not to reuse the same pilot sequence among users with higher interference.The simulation results show that the CPA algorithm proposed in this thesis can improve the minimum reachable rate of the system under the premise of less pilot overhead and it has higher pilot usage efficiency.3)Aiming at the complicated and immeasurable interference in heterogeneous cellular network Massive MIMO system,this thesis puts forward a pilot allocation algorithm based on greedy matching.The proposed algorithm transforms the pilot allocation problem into matching optimization problem through matching theory and combines greedy theory to find sub-optimal pilot allocation solution.When matching and modeling pilot problems,the algorithm defines many-to-one matching concepts,matching exchange conditions and pairwise stable matching concepts;Then,the user side utility function is defined by the binary network mapping theory and the utility function of the user side and the pilot side is used to determine whether the matching exchange is allowed;Finally,combining the algorithm with the greedy theory,the pairwise stable matching and the sub-optimal pilot allocation solution are acquired through the matching exchange.The simulation results manifest that the GMPA algorithm can effectively improve the performance of the system spectrum efficiency and pilot efficiency.