Pilot Assignment Approach For Pilot Contamination Mitigation In Multi-Cell Massive MIMO System

The rapid increase of mobile data traffic is a considerable challenge for the fifthgeneration(5G)cellular network.According to ongoing work,data traffic built up 69% in the year 2014,which indicates 30 times increase since 2000.It is predicted that this demand will still increase in the upcoming decades.However,current cellular network is incapable of supporting such a high data rate and spectral efficiency.To meet the demand for high data rate and spectral efficiency,time division duplex(TDD)massive multiple input and multiple output(m MIMO)systems has been recognized as a promising technology,which uses a large number of antennas at the base stations(BSs)to support massive users(UE).However,TDD mode is highly affected by pilot contamination(PC)which is caused by utilizing the same pilot sequences among the users in different cells.Thus,PC is a key problem in massive MIMO that can significantly degrade the system performance and needs to be addressed.In this dissertation,we propose a novel pilot assignment scheme “Hyper-Coloring-GraphPilot-Allocation(HCPA)” to suppress PC and to enhance the spectral efficiency(SE)of the system.According to this HCPA approach,the candidate UEs are divided into two zones based on their signal-to-interference-plus-noise ratio(SINR)i.e.,cell center and edge zones.Furthermore,an interference relationship graph with hyper-edges in order to confined minimum uplink rate is accomplished,and afterward,the pilot is assigned by employing the graph coloring approach.The simulation results show that the proposed algorithm can efficiently reduce PC,which can improve the system sum-rate.In addition,the proposed approach can keep lower mean squared error and normalized mean squared error(MSE)in a big SINR range,higher data rate,and better SE as compared to conventional pilot allocation techniques.