Phase Modulated Hybrid Precoding Design for Multi-RIS Aided Cell-Free mmWave MIMO System

Multiple reconfigurable intelligent surfaces (RISs) aided cell-free (CF) massive multiple input multiple output (MIMO) system has demonstrated its potential advantage in improving capacity and energy efficiency (EE). In this work, by deriving the upper and lower bounds of the asymptotic received power for double-hop signals, single-hop/multi-hop multi-RIS aided CF MIMO systems are theoretically discussed. On the basis of which, a phase modulation array (PMA) based hybrid precoding (HP) is proposed for single-hop RIS-aided CF massive MIMO system, in which PMA based RIS are employed to reduce energy consumption. Accordingly, a joint hybrid precoding and multi-RIS optimization problem is formulated to maximize the sum rate with regard to three variables (digital precoding, analog precoding, and RIS phase), and an alternating optimization algorithm is provided. To further reduce the computational complexity, a convolutional neural network (CNN) based method is proposed to seek the three-variable solution. Finally, simulation results verify that both schemes show superior performance in terms of sum rate and EE while the CNN based method exhibits fast convergence.