Research On The Performance Analysis And Power Allocation In Massive MIMO

Modern networks have extremely high requirements for data throughput,and 5G networks need to achieve a qualitative leap in spectrum efficiency to meet the growing demand for wireless traffic.Massive MIMO technology can increase the area throughput by several orders of magnitude by increasing the spectral efficiency of the system while using the same spectrum bandwidth and cell density as modern networks.Therefore,Massive MIMO has become one of the key technologies for 5G networks and has received important attention and research from academia and industry.This thesis firstly expounds the paradigm shift of MIMO technology and the key technologies and unique properties of Massive MIMO system,and conducts in-depth research on the two key issues of performance analysis and power allocation of the Massive MIMO system.Firstly,for the performance analysis of Massive MIMO system,this thesis conducts an extended research based on the performance analysis of Ngo Q under the physical channel model,and deeply analyzes the uplink spectrum efficiency performance of the multi-cell Massive MIMO system in a more realistic communication transmission environment.A non-universal uplink pilot-reuse scheme is employed during channel estimation phase.By using the asymptotically equivalent form in the random matrix theory,the closed-form expression of the ergodic reachable rate of the uplink data transmission in the multi-cell system is derived,and then the relationship between the spectrum efficiency of the multi-cell system and the system parameters such as the SINR(signal-to-interference-and-noise ratio),the channel dimension,the number of cell users,and the pilot reuse factor is analyzed.This expression has theoretical implications for how to properly set system parameters in practice to improve system performance.Compared with the traditional universal pilot-reuse scheme,by setting an appropriate pilot reuse factor,more orthogonal pilots can be generated and the distance between the cells reused same pilot subset becomes larger,thereby will significantly reduce the effects of pilot contamination and improve spectral efficiency performance.Secondly,for the power allocation algorithm of Massive MIMO,this thesis proposes a novel data and pilot joint iterative power allocation algorithm.Different from previous power allocation algorithms with traditional data or pilot,this thesis transforms the power control problem into an optimization problem that is constrained by the pilot and data power budget and aims to maximize the spectral efficiency weighted sum.To this end,this thesis derives the SINR lower bound expression for linear receiver with imperfect channel knowledge.By equivalently converting the derived SINR lower bound expression and using the standard interference function method,this thesis proposes a novel pilot and data joint iterative power allocation algorithm,which continuously iterates the user's data power and pilot power jointly,and uses the alternating optimization method to obtain the final approximate optimal solution,and discusses and proves the convergence of the algorithm.Compared with the traditional power allocation algorithm for pilot only or data only,the algorithm significantly improves the system spectral efficiency performance.