Reconfigurable Intelligent Surface for MISO Systems with Proportional\n Rate Constraints

Abstract

This paper investigates the system spectral efficiency (SE) in reconfigurable\nintelligent surface (RIS)-aided multiuser multiple-input single-output (MISO)\nsystems, where RIS can reconfigure the propagation environment via a large\nnumber of controllable and intelligent phase shifters. In order to explore the\nsystem SE performance behavior with user proportional fairness for such a\nsystem, an optimization problem is formulated to maximize the SE by jointly\nconsidering the power allocation at the base station (BS) and phase shift at\nthe RIS, under nonlinear proportional rate fairness constraints. To solve the\nnonconvex optimization problem, an effective solution is developed, which\ncapitalizes on an iterative algorithm with closed-form expressions, i.e.,\nalternatively optimizing the transmit power at the BS and the reflecting phase\nshift at the RIS. Numerical simulations are provided to validate the\ntheoretical analysis and assess the performance of the proposed alternative\nalgorithm.\n