Research On Low-Resolution Quantization And Space Time Codes For Massive MIMO System

In order to meet the requirements for high transmission rates of the fifth generation mobile communication technology(5G),more and more research focus on massive MIMO technology.It can effectively improve the spectral efficiency and energy efficiency by deploying a large-scale antenna array at the base station.Compared with the traditional massive MIMO system equipped one transmit and multiple receive antennas,massive MIMO system equipped multiple transmit and multiple receive antennas can achieve higher transmission gain.However,because the base station needs to be equipped with a large number of antennas,massive MIMO system has problems such as excessive hardware cost and excessive power consumption.It brings great difficulties to the actual deployment of massive MIMO systems.Therefore,it is worthy of study that how to reduce the circuit cost and power consumption of the massive MIMO equipped multiple transmit and multiple receive antennas while improving the system transmission performance.The main tasks of this dissertation are:1?From the perspective of how to improve system transmission performance and reduce system cost and power consumption,this dissertation takes the massive MIMO system equipped multiple transmit and multiple receive antennas as the research object,and designs a structure that uses Alamouti coding to achieve diversity transmission while using low-resolution quantization at the base station.Low-resolution quantization effectively reduces system power consumption and cost.First,we get the expression of the uplink spectral efficiency of the system through Rice fading channel;then random matrix theory is applied to derive the approximate expression;based on the approximate expression,we further analyzed the parameter in the system.Simulation results show that the use of Alamouti coding in massive MIMO system equipped multiple transmit and multiple receive antennas can improve transmission performance.At the same time,the introduction of low-resolution quantization can effectively reduce system power consumption and cost.And as the number of receiving antennas at the base station increases,the system capacity also gradually increases.When the number of antennas is large enough,the error introduced by low-resolution quantization can be ignored.2 ? Although low-resolution quantization can greatly reduce system cost and power consumption,the pure low-ADC structure also brings a series of problems,for example,related signal processing algorithms are no longer applicable,channel estimation is difficult,and so on.In view of the above problems,this dissertation studies the method of using a mixed-ADC structure to improve system performance,that is,retaining a part of ADC with high-resolution ADC at the receiver.With the help of random matrix theory,the approximate expression of the spectral efficiency of the massive MIMO system based on mixed-ADC structure and Alamouti coding is obtained.Simulation results show that compared with the pure low-ADC structure,the mixed-ADC structure can achieve better performance in the Alamouti coded massive MIMO system.At the same time,the system cost and the complexity of the hardware circuit can be effectively reduced.Moreover,by using mixed-ADC architecture,a better trade-off between spectral efficiency and energy efficiency can also be obtained.In summary,for the massive MIMO system equipped multiple transmit and multiple receive antennas,this dissertation proposes a structure that uses Alamouti coding to achieve diversity transmission,and uses low-resolution quantization technology at the base station,which effectively improves the system performance and reduces system cost and power consumption.