Research On Energy Efficiency Joint Optimization Of Large-scale MIMO System

Massive Multiple-Input Multiple-Output(MIMO)technology has become one of the key technologies of 5G communication networks with its excellent performance.By equipping the base station(BS)with a large number of antennas to improve the spatial gain and diversity gain of the receiver,the system performance is greatly improved,and the increasing network demand problem is solved very well.However,the huge power consumption caused by the huge antenna system at the base station has also aroused widespread concern in academic circles,so how to reduce power consumption while ensuring high system performance has become one of the urgent problems to be solved.With this background,this thesis makes the following research on the wireless communication system using massive MIMO technology and puts forward the related energy efficiency(EE)optimization scheme.Aiming at the problems of low-precision analog-to-digital converter(ADC)architecture leading to small system capacity and high-precision ADC architecture leading to excessive system power consumption.In this thesis,a massive MIMO system based on mixed-precision ADC architecture is considered.For the uplink of this system,first,the approximate expression of EE is derived based on the maximum ratio combining(MRC)acceptance algorithm at the BS.Then,the proportion of highprecision ADC in mixed-precision ADC architecture is determined.For maximize the EE,the number of antennas at the base station,the transmission power of users,and the quantization accuracy of lowprecision ADC are taken as optimization parameters.Based on the Dinkebach algorithm,an alternating iterative algorithm of multi-parameter joint optimization is proposed.Furthermore,the influence of the ratio of high-precision ADC on the Spectral Efficiency(SE)and EE of the system is analyzed.The effectiveness of the algorithm is verified by simulation,which can greatly improve the EE of the system.It also can make a good compromise between the EE and the SE of the system by adjusting the ratio of high-precision ADC.In view of the large-scale cellular-free MIMO system with multi-antenna Access Point(AP)and full low-precision ADC architecture at the base station,this thesis considers the five-parameter resource allocation problem of low-precision quantization bits at the receiver,user transmission power,pilot length,the number of AP points and the number of antennas,and proposes a resource allocation optimization algorithm.First,the minimum mean square error estimation(MMSE)method is used to estimate the channel to obtain CSI,and the signal received by AP point is detected and recovered by MRC receiving algorithm,so as to derive the approximate closed expressions of the achievable rate of the system uplink and the system power consumption.Establishing an energy efficiency optimization model with the constraint conditions of transmission power and pilot length;Then,the energy efficiency expression in fractional form is transformed into a reduced form by fractional programming.Prove the convex function properties of related parameters,and transform the objective function into the difference of convex functions(D.C)of related parameters,so as to solve the corresponding optimization problems by D.C programming in the follow-up: under the condition of controlling the number of quantization bits and AP points,update the remaining three variables in a cyclic iteration to get the optimal system energy efficiency value.From the simulation results,it can be seen that the algorithm can effectively improve the EE and SE of the system,and on this basis,it takes into account the fairness among users.