Research On Capacity Analysis And Precoding Algorithm In The Massive MIMO

With the rapid growth of the number of wireless mobile communication devices,more and more people have put forward higher requirements for the speed of wireless mobile communication systems.Considering that large-scale multiple-input multiple-output(MIMO)technology can effectively improve the array gain and spatial resolution of mobile communication systems,when the communication system is interfered by strong users,it can still maintain high robustness,resulting in system transmission rate.And the capacity has reached an order of magnitude improvement.However,as the number of base station antennas and the number of users in the system increase,so does the various interferences and power consumption in the system,which adversely affects system performance.How to improve system capacity based on reducing interference and energy consumption has become the focus of contemporary research.To this end,based on the existing large-scale MIMO system model,this paper makes an in-depth analysis and proposes corresponding improvement methods.(1)Capacity analysis of multi-cell multi-user massive MIMO uplink and downlink systems.In multi-cell multi-user cellular network mobile communication systems,linear detectors and precoding techniques are critical to large-scale MIMO system capacity.Aiming at the above problems,the system capacity of massive MIMO uplink(UL)and downlink(DL)is analyzed under the uncorrelated Rayleigh fading channel model.In the analysis process,the MMSE is used to estimate the channel,and the uplink and downlink are derived.The road traverses the capacity expression and experimentally simulates the performance results of several linear precoders and detectors.The experimental results show that the MMSE detection technology is the best in the uplink and the RZF precoding technology in the downlink is the best in the case of pilot pollution.(2)Capacity analysis of multi-user multi-cell massive MIMO system based on incomplete CSI.Based on how to design an efficient precoding algorithm and obtain relatively complete channel state information,this paper studies under the multi-user multicell system model,gives the estimated characteristic parameters of channel state information(CSI),and then studies the large-scale.System capacity for MIMO.In addition,based on the comprehensive consideration of the number of base station antennas,the number of users andthe pilot reuse factor,their configuration relationships are optimized.The experimental results show that the precoding algorithm and the rate of the precoding algorithm are better than those in the unknown CSI under the condition of known CSI.As the channel estimation characteristic parameter increases,the spectral efficiency of the precoding algorithm decreases.(3)Massive MIMO power allocation scheme and energy efficiency study of hybrid resolution ADC/DAC.The bottleneck of actual large-scale multi-input multi-output system technology is caused by high power consumption and expensive hardware.We consider a multi-pair massive MIMO relay system architecture with a mixed analog-to-digital converter/digital-to-analog converter,some of which are connected to a low-resolution ADC/DAC,while the remaining antennas are connected to a high-resolution ADC./DAC.In this paper,an efficient power allocation scheme is proposed.The standard convex optimization tool mathematical algorithm is used to solve the complementary geometric programming problem,and the most effective power allocation method is obtained.By compensating the low resolution ADC,the relay system and the rate reach a good one.effect.Finally,the power consumption of different numbers of low-resolution ADC/DAC is studied by deriving energy efficiency.Experimental simulation results show that a large antenna array can be used to implement a hybrid ADC/DAC architecture,significantly reducing the power consumption of an actual large-scale MIMO system.From the aspects of precoding,system capacity and power loss,the problems in the large-scale MIMO system are comprehensively analyzed.A series of experimental simulations are carried out to improve the power loss in the actual process.