Research On Precoding Technique Based On Multi-cell Cooperation For Massive MIMO Systems

As a key technology of 5G,Massive MIMO can effectively improve system capacity,throughput,link transmission reliability,spectrum efficiency and energy efficiency.But Massive MIMO technology also faces many problems and challenges.In multi-cell Massive MIMO systems,the influence of inter-cell interference and intra-cell interference increases with the number of transmitting antennas and users increasing.So interference management technology is essential in multi-cell Massive MIMO systems.In additon,each transmitting antenna connects with two DACs and one RF chain.Because of a large number of transmitting antennas,there need to be considerable DACs and RF chains in Massive MIMO systems.This will cause a great deal of cost and power consumption.Using low-resolution DACs is an effective solution to solve the problem,which not only reduces the power consumption and cost of DACs,but also simplifies the design of RF chain.However,it will cause large non-linear quantization distortion and seriously affect the performance of precoding algorithms.So the precoding algorithm under quantization distortion has attracted more and more attention.Precoding algorithms in low resolution DACs multi-cell Massive MIMO systems are studied in this paper.Precoding algorithms can be divided into linear precoding algorithms and nonlinear precoding algorithms.Because of its huge complexity,nonlinear precoding algorithms are not practical in Massive MIMO systems.So,the paper focuses on Linear precoding algorithms.In terms of interference management,the paper considers coorperative precoding algorithms sharing channel information among base stations to suppress inter-cell interference.It is known that low resolution DACs lead to large nonlinear quantization distortion and reduce the performance of precoding algorithm.So far,many literatures have studied the precoding algorithm in single cell Massive MIMO systems with low resolution DACs.WFQ algorithm,which takes into account the quantization effect,is a linear precoding algorithm based on MMSE criterion.It can restrain quantization distortion to some extent.In this paper,WFQ algorithm is extended to multi-cell Massive MIMO systems with low resolution DACs,then WFQ-BF precoding algorithm is proposed.Compared with classical ZF-BF algorithm,WFQ-BF precoding algorithm can additionally suppress the interference caused by quantization distortion.The simulation results show that the WFQ-BF algorithm has obvious advantages compared with ZF-BF algorithm when the number of users is large in multi-cell Massive MIMO systems with low resolution DACs.For ZF-BF algorithm,WFQ-BF algorithm and many other precoding algorithms,matrix inversion is inevitable.Due to the large number of transmitting antennas and users in Massive MIMO systems,the matrix size that needs to be inverted in precoding algorithms becomes very large,especially in multi-cell cooperative precoding algorithms.How to quickly inverse matrix with low computing complexity is one of the keys to apply Massive MIMO technology in practical systems.Compared with the direct matrix inversion algorithms,the iterative matrix inversion algorithms have the advantages of small storage space and high computational efficiency,which makes the iterative inversion algorithm more popular in large-scale matrix inversion.Newton iterative algorithm is a classical algorithm of the iterative inversion algorithms.It has the advantages of high computational efficiency and strong stability.Based on Newton's iteration algorithm,a variable step size iteration algorithm is proposed in this paper.By analyzing the error matrix,the update formula of the step size is given,which greatly speeds up the convergence rate of the algorithm,at the cost of slightly increasing the complexity.