Low Complexity Precoding Algorithm Design for RIS-aided Cell-free Massive MIMO Systems
In this paper,we consider a Reconfigurable Intelligent Surface(RIS)-aided Cell-free massive Multiple-Input Multiple-Output(CF mMIMO)communication system,and propose a low-complexity precoding and RIS reflection phase shifts Alternating Opti-mization(AO)algorithm.In order to solve the problem that traditional Regularized Zero Forming(RZF)precoding algorithm is too complex,we propose a low-complexity RZF-CG precoding algorithm using the Conjugate Gradients(CG)method,which converts the in-verse matrix of RZF precoding into a linear equation system minimization problem,derives the residuals of the algorithm to update the search direction,and iteratively solves the inverse matrix.With the goal of maximizing the total spectral efficiency of the system user,we derive the RIS phase closed-form expression and then propose a low-complexity Projected Gradient Ascent(PGA)algorithm based on statistical channel state information.Simulation results show that the proposed AO algorithm can not only effectively improve system per-formance,but also reduce the algorithm complexity by about 73.2%.
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