8 May 2024 | Anastasios Papazafeiropoulos, Jiancheng An, Pandelis Kourtessis, Tharmalingam Ratnarajah, Symeon Chatzinotas
This paper explores the use of stacked intelligent metasurfaces (SIMs) to enhance the performance of holographic multiple-input multiple-output (HMIMO) communications. The authors formulate a joint optimization problem to maximize the achievable rate by optimizing the covariance matrix of the transmitted signal and the phase shifts at both the transmitter and receiver SIMs. They propose an iterative projected gradient algorithm to solve this nonconvex problem, derive the gradients and projection expressions, and determine the step size to ensure convergence. Simulation results show that the proposed algorithm converges faster and achieves the same rate as the alternating optimization (AO) method with fewer iterations, demonstrating the effectiveness of the SIM-assisted HMIMO system.This paper explores the use of stacked intelligent metasurfaces (SIMs) to enhance the performance of holographic multiple-input multiple-output (HMIMO) communications. The authors formulate a joint optimization problem to maximize the achievable rate by optimizing the covariance matrix of the transmitted signal and the phase shifts at both the transmitter and receiver SIMs. They propose an iterative projected gradient algorithm to solve this nonconvex problem, derive the gradients and projection expressions, and determine the step size to ensure convergence. Simulation results show that the proposed algorithm converges faster and achieves the same rate as the alternating optimization (AO) method with fewer iterations, demonstrating the effectiveness of the SIM-assisted HMIMO system.