Research On The Pilot Decontamination Algorithm For Multi-cell Multi-user Massive MIMO Systems

Massive multiple-input multiple-output(MIMO)technology is one of the core technologies of the fifth generation(5G)cellular mobile communication,which obtained a large amount of space degree of freedom by configuring massive antenna array on the base station.Massive MIMO use the same time-frequency resources to provide access services for multiple users,which can increase the number of user connections and system capacity.In a multi-cell multi-user massive MIMO system,the base station needs to perform channel estimation with pilot assistance because of the high channel dimension,and then perform uplink reception detection and downlink precoding using channel state information(CSI).However in mobile communication applications,the pilot sequence length and the pilot set size are limited by the short channel coherence time,pilot contamination(PC)caused by inter-cell pilot reuse may lead to channel estimation error,which affecting the performance of communication.This thesis focus on the multi-cell multi-user massive MIMO system,which research the pilot decontamination algorithm by analyzing the causes of pilot contamination.The main research contents are as follows:(1)Pilot decontamination in multi-cell multi-user massive MIMO systems is researched from the perspective of pilot allocation.In order to maximize the uplink sum rate,a pilot decontamination algorithm based on matched game(PA-MG)between users and pilots is proposed.The algorithm consists of two steps: firstly,the user side generates a preference list for the available pilots based on the user utility function,and applies for the optimal pilot in the preference list;secondly,the base station side generates a preference list for the requesting users based on pilot utility functions,assigning the pilot to the optimal arranged user until all users is assigned.The simulations choose the uplink SINR?achievable rate and the convergence time as metrics,analyze and evaluate the performance of the proposed PA-MG algorithm compared with the RPA algorithm,PGPA algorithm,and WGC-PD algorithm.(2)One main drawback of the weighted graph coloring based pilot decontamination(WGC-PD)algorithm proposed in literature [23] is that the allocation ignores the users of lower potential pilot contamination,which allocates the pilot of lower interference for the user of higher potential pilot contamination sequentially.This thesis proposes an improved weight graph coloring pilot allocation(IWGCPA)algorithm,which sets a screening method to allocate better pilot for the users of lower potential pilot contamination based on literature [23].Then a mathematical formulation of optimization issue was provided with the objective of minimizing the pilot contamination by adjusting pilot power between users after the IWGCPA algorithm,which further to improve channel estimation performance,and maximize uplink achievable rate.The simulations choose the channel estimation normalized MSE?uplink SINR and achievable rate as metrics,analyze and evaluate the performance of the proposed algorithm compared with the RPA algorithm,and WGC-PD algorithm,IWGCPA algorithm.