Large-scale MIMO Energy Efficiency Optimization Methed With Non-ideal Parameters

Compared with the traditional multi user MIMO system,system capacity is improved and transmit power is reduced by increasing the number of transmit antennas at base station,which can meet the high demand of the fifth generation mobile communication for the Spectral efficiency and energy efficiency simultaneously.But the larger number of transmit antennas means more radio frequency links and more energy consumption,which leads to the decrease of the energy efficiency of the system.Considering the circuit power parameters and channel state information(CSI)in real massive MIMO system are often imperfect,the paper study the energy efficiency optimization schemes for massive MIMO systems under non-ideal parameters.The main contributions of this work are summarized as follows:Firstly,the massive MIMO system model,power consumption model and three common energy efficiency methods of large-scale MIMO are introduced.Considered the non-ideal circuit power parameters,we first establish an energy efficiency optimization model.Then by analyzing the characters of the optimized objective function and using the direct derivation method,the base station transmit power(closed-form solution)expression is obtained.Next,we discuss the influence of non-ideal circuit power parameters on the energy efficiency of the system.At the same time,an energy efficiency optimization method based on statistical average is proposed under the unknown circuit power consumption parameters,the results of which are infinitely close to the energy efficiency of the system with the real circuit power consumption.Secondly,for the channel estimation error,the capacity formula of massive MIMO under no-perfect CSI is deduced with two different precoding methds: zero forcing and maximum ratio transmit.Then the effect on energy efficiency of the system is analyzed by the simulation results.Next,we transform the original NP problem into a linear solvable problem and prose a robust beamforming algorithm based on the fractional programming theory and the relationship between the user's SINR and the minimum mean square error.Last,using the Lagrangian dual method and KKT conditions,the optimal energy efficiency beamforming algorithm is obtained,which can greatly improve the performance of the system.We also discusses the computational complexity of the algorithm.Finally,Considered the high computational complexity and high power consumption of RF links in massive MIMO system,in this paper,using the antenna selection to optimise the sysytem energy efficiency.A low complexity method for determining the optimal antenna subset of system is proposed under no-perfect CSI.,then a method of combining antenna selection and beamforming is proposed,which can not only improve the energy efficiency of the system,but also reduce the computational complexity of the system greatly.