Joint hybrid-precoding design for MU-MISO systems with a subconnected architecture

In this study, we propose a joint hybrid-precoding algorithm for multiuser multiple-input single-output downlink systems. Specifically, we consider that the base station employs an energy-efficient hybrid-precoding subconnected (SC) architecture with fixed equal subarrays (FESA) (SC-FESA). Optimizing the analog precoding matrix in an SC-FESA architecture is challenging due to its unique constraint structure. In this study, to maximize system sum rate, we propose an efficient method to transform the system’s sum-rate optimization problem into a continuous and differentiable objective function wherein only the nonzero elements of the analog precoding matrix are optimized. For the formulated problem, we develop an alternating optimization (AO) approach to jointly optimize the digital and analog precoders in succession by maximizing the system’s sum rate. Specifically, in the proposed AO method, when the digital precoder is fixed, we employ the Riemannian conjugate gradient algorithm to generate the analog precoder. Furthermore, when the analog precoder is fixed, we use the minimum mean squared error method to obtain the digital precoder. Numerical simulation results show that the proposed AO algorithm improves the sum rate and energy efficiency of the SC-FESA architecture compared to existing algorithms.