RIS-aided Wireless Communications: Can RIS Beat Metal Plate?

Reconfigurable Intelligent Surface (RIS) has recently been regarded as a paradigm-shifting technology beyond 5G, for its flexibility on smartly adjusting the response to the impinging electromagnetic (EM) waves. Usually, RIS can be implemented by properly reconfiguring the adjustable parameters of each RIS unit to align the signal phase on the receiver side. And it is believed that the phase alignment can be also mechanically achieved by a metal plate with the same physical size. However, we found in the prototype experiments that, a well-rotated metal plate can only approximately perform as well as RIS under limited conditions, although its scattering efficiency is relatively higher. When it comes to the case of spherical wave impinging, RIS outperforms the metal plate even beyond the receiving near-field regions. We analyze this phenomenon with wave optics theory and propose explicit scattering models for both the metal plate and RIS in general scenarios. Finally, the models are validated by simulations and field measurements.

MmWave MIMO Communication with Semi-Passive RIS: A Low-Complexity Channel Estimation Scheme

Reconfigurable intelligent surfaces (RISs) have recently received widespread attention in the field of wireless communication. An RIS can be controlled to reflect incident waves from the transmitter towards the receiver; a feature that is believed to fundamentally contribute to beyond 5G wireless technology. The typical RIS consists of entirely passive elements, which requires the high-dimensional channel estimation to be done elsewhere. Therefore, in this paper, we present a semi-passive large-scale RIS architecture equipped with only a small fraction of simplified receiver units with only 1-bit quantization. Based on this architecture, we first propose an alternating direction method of multipliers (ADMM)-based approach to recover the training signals at the passive RIS elements, We then obtain the global channel by combining a channel sparsification step with the generalized approximate message passing (GAMP) algorithm. Our proposed scheme exploits both the sparsity and low-rankness properties of the channel in the joint spatial-frequency domain of a wideband mmWave multiple-input-multiple-output (MIMO) communication system. Simulation results show that the proposed algorithm can significantly reduce the pilot signaling needed for accurate channel estimation and outperform previous methods, even with fewer receiver units.