How Much Time Is Required for Phase Shift Delivery in RIS-Aided Wireless Systems?

Reconfigurable intelligent surface (RIS) has become a focal point of extensive research due to its remarkable “squared gain”. However, achieving a substantial beamforming gain typically requires a significant number of elements, which leads to a non-negligible overhead that forwards the coherent phase shift to the RIS. Different from previous works, which primarily focus on the information transmission phase, we consider the phase delivery overhead during the phase-shift delivery phase to explore the trade-off between performance and overhead. To reduce the phase delivery overhead via the control link, we introduce a hybrid phase shift mechanism, encompassing both the coherent and fixed phase shifts. Specifically, a beamforming problem is formulated for maximizing the throughput. In light of the intractability of the problem, we develop an alternating optimization-based iterative algorithm by combining quadratic transformation and successive convex approximation. To gain more insights, we derive the closed-form expression of the number of elements adopting the coherent phase shift in the large signal-to-noise ratio region. This expression serves as a valuable guide for the practical implementation of the RIS technology. Our simulation results conclusively demonstrate the effectiveness of the proposed algorithm in achieving a favorable trade-off between throughput and overhead. Furthermore, the introduction of the hybrid phase shift approach significantly reduces phase delivery overhead while concurrently enhancing the system throughput.

I. Introduction

Recently, reconfigurable intelligent surface (RIS) has garnered substantial attention from both academia and industry due to its remarkable attributes including high array gain and low power consumption [1]. The RIS can passively reflect the received signal and achieve “squared gain” without extra transmit power and channel bandwidth resources by simply adjusting the phase shift of each reflecting element. So far, there have been numerous efforts to apply the RIS to various network scenarios, such as mmWave communication [2], wireless-powered communication [3], and to improve the performance and efficiency of communication systems by optimizing different performance metrics, such as the age of information [4], energy efficiency [5], deployment location [6].