Reconfigurable Intelligent Surface for MISO Systems with Proportional Rate Constraints

Abstract

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

This paper appears in the Proceedings of IEEE International Conference on Communications (ICC) 2020. Please feel free to contact us for questions or remarks

References in corpus (2)

• Weighted Sum-Rate Optimization for Intelligent Reflecting Surface Enhanced Wireless Networks
• Reconfigurable Intelligent Surfaces based RF Sensing: Design, Optimization, and Implementation

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• Reconfigurable Intelligent Surface assisted Multi-user Communications: How Many Reflective Elements Do We Need?