Reconfigurable Intelligent Surface for Near Field Communications: Beamforming and Sensing

Abstract

Reconfigurable intelligent surface (RIS) can improve the communications between a source and a destination. The surface contains metamaterial that is configured to reflect the incident wave from the source towards the destination, especially when there is a blockage in between. Recently, continuous aperture RIS is proved to have better communication performance than discrete aperture RIS and has received much attention. However, the conventional continuous aperture RIS is designed to convert the incoming planar waves into the outgoing planar waves, which is not the optimal reflecting scheme when the receiver is not a planar array and is located in the near field of the RIS. In this paper, we consider two types of receivers in the radiating near field of the RIS: (1) when the receiver is equipped with a uniform linear array (ULA), we design RIS coefficient to convert planar waves into cylindrical waves; (2) when the receiver is equipped with a single antenna, we design RIS coefficient to convert planar waves into spherical waves. Simulation results demonstrate that the proposed scheme can reduce energy leakage at the receiver and thus enhance the channel capacity compared to the conventional scheme. More interestingly, with cylindrical or spherical wave radiation, the power received by the receiver is a function of its location and attitude, which could be utilized to sense the location and the attitude of the receiver with communication signaling.

Design of Near-Field Beamforming for Large Intelligent Surfaces

“…However, as we see from the simulation results of array gains in the next, setting K = 10 is sufficiently good for the interval (5,200]m. That means, in practice the codebook size of the 1D near-field BF can be made very small.…”

“…The codebooks are designed for an interval (5,200]m. Firstly, it can be seen that the codebook optimized with Algorithm 1 outperforms the uniform codebook with the same size K = 5, while the gains become smaller for K = 10.…”

Design of Near-Field Beamforming for Large Intelligent Surfaces

“…Recently, the concept of Large Intelligent Surface (LIS) [2]- [4] arises as an evolution of massive multi-input multi-output (MIMO) system, which shows substantial gains in performances of signal-transmission and terminal-positioning. Later on, similar concepts such as reflection intelligent surface (RIS), intelligent reflection surface (IRS), holographic MIMO [5]- [8] and others have also been introduced and gained extensive interests from researchers in different areas.…”

“…Although near-field BF has been studied in literature e.g., [5], [6], [14], [16]- [18], [25]- [27], to our best knowledge, it has not been considered from a practical implementation perspective that can cooperate with the existing far-field BF scheme such as in 5G-NR. For instance, in [14], the near-field BF vector for a microphone-array in an acoustic system is derived to be equal to the signal propagation vector, which is however, unknown at the transmitter side.…”

“…For instance, in [14], the near-field BF vector for a microphone-array in an acoustic system is derived to be equal to the signal propagation vector, which is however, unknown at the transmitter side. In [5] and [6], the near-field BF is designed for a RIS that cooperates with a next-generation NodeB (gNB), which shows that the optimal BF weights depend on the distances among a gNB, a RIS, and a UE. Nevertheless, the design in [5] uses an estimate of distance measured from sensing, while in [6] the BF vector utilizes a codebook based approach with assistance and feedbacks from the UE.…”