Research On Performance Of Sparse Antenna Array

As an effective method to increase the capacity of a cellular network system,large-scale Multiple-Input Multiple-Output(MIMO)technology has been widely used in the field of mobile communications,and the number of antenna elements on the base station side keeps increasing with the requirements for performance.However,the ever-increasing number of antenna elements has led to the continuous increase in cost and power consumption.Therefore,some people in the industry have taken a new approach and proposed to sparse large-scale antenna arrays.In the case of reducing the number of antennas,using methods such as array element position optimization to reduce the number of antennas,the performance of the sparse antenna array is close to that of a uniform array with a large number of antennas.In the 6G standardization research stage,important technologies such as sparse antenna arrays communicating with terahertz and orbital angular momentum have received extensive attention from the industry.Aiming at the application of sparse antenna arrays in massive MIMO scenarios,this paper first uses the iterative convex optimization algorithm and particle swarm algorithm to construct two antenna arrays,linear arrays and panel arrays,and uses a system-level simulation platform to generate the results of these two algorithms.The performance of the sparse antenna array is analyzed and compared with the uniform array before sparse.Then an improved algorithm and antenna array for further optimization based on the system-level simulation results are proposed.The main contributions of this article are as follows:(1)The current academic research on sparse antenna arrays under massive MIMO is relatively limited,and most of the studies are in scenarios such as radar or sensors,which are quite different from MIMO in mobile communications.Therefore,in the face of mutual interference between base stations in mobile communications,and restrictions on the geometric size of antenna panels,this paper introduces iterative convex optimization algorithm and particle swarm algorithm for the application of sparse antenna arrays in cellular networks.By setting reasonable optimization goals and boundary conditions,the two algorithms can generate a sparse antenna array corresponding to the original uniform array.The simulation proves that,when the number of antennas is reduced,the width of the main lobe and the maximum sidelobe level of the sparse antenna array can still be close to the level of the uniform array before the sparse.(2)In view of the situation that most of the current sparse antenna array research stops at the theoretical analysis and antenna pattern simulation stage,this paper builds an NR system-level simulation platform,and inputs the sparse antenna array obtained by the above optimization algorithm into the platform.In actual scenarios,referring to the simulation requirements standardized by the International Telecommunication Union(ITU),the simulation performance of the sparse antenna array and its corresponding uniform array is analyzed,and the layout of the sparse antenna array is further optimized based on the simulation results.Array.The simulation results show that a base station with a sparse antenna array can provide a system capacity close to that of a uniform array base station with fewer antenna elements.