RIS辅助的无蜂窝大规模MIMO关键技术研究OA

To address the interference-limited problem in dense cellular networks,cell-free massive MIMO leverages large-scale macro-diversity to construct a novel user-centric architecture,which significantly improves the performance of each user through large-scale flexible collaboration.Simultaneously,cell-free is complemented by reconfigurable intelligent surface to greatly enhance network capacity at low cost and low power consumption.This paper focuses on two key issues of antenna calibration and pilot allocation for RIS-aided cell-free massive MIMO.For the problem of large-scale RAU calibration,firstly,under the constraints of minimum calibration signal-to-noise ratio and calibration coherence time,a clustering-based self-healing calibration topology construction method is proposed.Then,to reduce the time cost of calibration,the intra-cluster and inter-cluster calibration timing is designed,and an extensible antenna calibration algorithm is studied,which can achieve joint phase calibration of an arbitrary number of RAUs.For the problem of pilot allocation,a new method for constructing dynamic user clusters based on spatial high correlation is proposed firstly.Then,a pilot allocation method is proposed based on the minimum channel correlation within user clusters and the minimum multiplexing probability among user clusters.The simulation results show that the proposed calibration algorithm has a small calibration error and good scalability.Moreover,the proposed pilot allocation algorithm closely approaches the performance of the maximum capacity pilot allocation algorithm,and its complexity is significantly reduced.