Intelligent Omni-Surfaces: Ubiquitous Wireless Transmission by Reflective-Refractive Metasurfaces

• Published in: IEEE transactions on wireless communications Vol. 21; no. 1; pp. 219 - 233
• Main Authors: Zhang, Shuhang, Zhang, Hongliang, Di, Boya, Tan, Yunhua, Di Renzo, Marco, Han, Zhu, Vincent Poor, H., Song, Lingyang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: analog and digital beamforming; Array signal processing; Beamforming; Communication; Communication systems; Communications systems; Design optimization; Downlink; Intelligent omni-surface; Iterative algorithms; Metasurfaces; Optimization; phase shift design; PIN photodiodes; Radio transmission; Surface waves; Wave propagation; Wireless communication; Wireless communications
• ISSN: 1536-1276; 1558-2248
• DOI: 10.1109/TWC.2021.3094869

Intelligent reflecting surfaces (IRSs), which are capable of adjusting radio propagation conditions by controlling the phase shifts of the waves that impinge on the surface, have been widely analyzed for enhancing the performance of wireless systems. However, the reflective properties of widely studied IRSs restrict the service coverage to only one side of the surface. In this paper, to extend the wireless coverage of communication systems, we introduce the concept of intelligent omni-surface (IOS)-assisted communication. More precisely, an IOS is an important instance of a reconfigurable intelligent surface (RIS) that can provide service coverage to mobile users (MUs) in a reflective and a refractive manner. We consider a downlink IOS-assisted communication system, where a multi-antenna small base station (SBS) and an IOS jointly perform beamforming, for improving the received power of multiple MUs on both sides of the IOS, through different reflective/refractive channels. To maximize the sum-rate, we formulate a joint IOS phase shift design and SBS beamforming optimization problem, and propose an iterative algorithm to efficiently solve the resulting non-convex program. Both theoretical analysis and simulation results show that an IOS significantly extends the service coverage of the SBS when compared to an IRS.