| Energy efficiency optimization problem of massive MIMO system is one of the key contents of current 5G research.At present,most of the researches on energy efficiency optimization are based on full-precision ADC quantization.However,with the rapid increase of traffic in wireless communication,using full-precision ADC quantization will bring high hardware cost and a large amount of energy consumption.Using low-precision ADC for quantitative processing can effectively reduce the cost of hardware and energy consumption of the system,but it will bring some performance losses.Therefore,this paper focuses on the energy efficiency optimization of massive MIMO systems with low-precision ADCs.Firstly,based on the known CSI and unknown CSI,the energy efficiency resource allocation scheme of large-scale MIMO system with low-precision ADC is studied under MRC detection.In order to improve the performance of the system,this paper further studies the energy efficiency optimization of low-precision ADC massive MIMO system under low complexity ZF detection.The first chapter describes the research background,the opportunities and challenges faced by massive MIMO system,the research status of energy efficiency optimization problem and low-precision quantification techniques.In the second chapter,firstly,the fading characteristics and classification in wireless communication system are introduced,secondly,the channel model of large-scale MIMO system is introduced,and the detection matrix of MRC detection algorithm,ZF detection algorithm and MMSE detection algorithm is briefly deduced.Then the low-precision quantization technology is introduced,and the basic principle of ADC and aqnm model are analyzed.Finally,the energy efficiency optimization model and convex optimization problem of large-scale MIMO system are introduced.In the third chapter,the energy efficiency of massive MIMO systems with low-precision ADCs based on MRC detection is studied.Firstly,a single-cell massive MIMO system with known CSI is proposed to maximize the energy efficiency.And the number of base station antennas is optimized,and the proposed scheme further considers the limitation of the user transmit power and the number of base station antennas under the constraint of the minimum transmission power of the user,thereby establishing an energy efficiency optimization model,and respectively adopting the Lagrangian method for transmitting The power distribution and the three-point method optimize the number of base station antennas,so that the system can obtain the maximum energy efficiency value.Secondly,considering a CSI unknown massive MIMO system,considering the influence of channel estimation,under the user power limitation and pilot sequence length limitation,an energy efficiency optimization model is established,and the alternating optimization algorithm is used to optimize the pilot length and data transmission power.The number of quantization bits is jointly optimized.The fourth chapter discusses the energy efficiency of low-precision ADC massive MIMO systems under ZF detection.In the massive MIMO uplink,ZF is used to detect the received signal of the base station,and a low-complexity ZF detection algorithm is used to effectively reduce the complexity of the direct inversion of the large matrix,and the analytical formula of the system spectrum efficiency and the total system power consumption is derived.In order to ensure the normal operation of the communication,the proposed scheme not only limits the maximum transmission power,but also limits the minimum transmission power,and establishes an optimization model aiming at maximizing energy efficiency.On this basis,the gradient of the user is used to iteratively optimize the transmit power of the user.The fifth chapter summarizes and forecasts,summarizes the inadequacies of the research content of the thesis,and proposes an open question that needs to be solved urgently. |
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