Reconfigurable intelligent surfaces for smart wireless environments: channel estimation, system design and applications in 6G networks

Abstract

Reconfigurable intelligent surface (RIS), one of the key enablers for the sixth-generation (6G) mobile communication networks, is considered by designers to smartly reconfigure the wireless propagation environment in a controllable and programmable manner. Specifically, an RIS consists of a large number of low-cost and passive reflective elements (REs) without radio frequency chains. The system gain of RIS wireless systems can be achieved by adjusting the phase shifts and amplitudes of the REs so that the desired signals can be added constructively at the receiver. However, an RIS typically has limited signal processing capability and cannot perform active transmitting/receiving in general, which leads to new challenges in the physical layer design of RIS wireless systems. In this paper, we provide an overview of the RIS-aided wireless systems, including the reflection principle, channel estimation, and system design. In particular, two types of emerging RIS systems are considered: RIS-aided wireless communications (RAWC) and RISbased information transmission (RBIT), where the RIS plays the role of the reflector and the transmitter, respectively. We also envision the potential applications of RIS in 6G networks.

Vision, application scenarios, and key technology trends for 6G mobile communications

“…RIS, with a "reconfigurable/programmable wireless transmission channel" as the core, opens a new direction for future networks owing to its intrinsic characteristics, including low cost, low energy consumption, high reliability, and large capacity [17]. Authors in [18] provided an overview of the fundamental physical layer issues of the RIS-assisted wireless systems, including the reflection principle, channel estimation, and system designs for RIS-aided wireless communication where RIS acts as a reflector and RIS-based information transmission where RIS functions as a transmitter. Moreover, several potential applications of RIS in 6G have been proposed.…”

MIMO Channel Estimation using Score-Based Generative Models

“…where the term ψ Y is omitted since it does not depend on the current H. Finally, notice that there is now an additional term when compared to (8): α • ψ Y |H updates the current estimate in a direction that makes it more consistent with the received pilots Y. Taken together, the three updates in (10) represent the core routine of the proposed channel estimation algorithm.…”

“…With the deployment of millimeter wave (mmWave) band communications, recovering accurate, high-dimensional channel state information (CSI) using reduced pilot overhead has become a major open research problem [3]- [5]. For example, reflective intelligent surfaces -equipped with up to hundreds of antennas -are an active area of research for high-dimensional wireless systems [6], [7], where channel estimation has been recently investigated using either optimization approaches [8] or data-driven methods [9], [10]. Estimating accurate CSI using data-driven methods is envisioned as an important area of research for future communication systems that integrate artificial intelligence in physical layer processing [1], [11], including being taken into consideration for standardization [12].…”

Reconfigurable Intelligent Surfaces for 5G and beyond Wireless Communications: A Comprehensive Survey

“…As a result, the reflected radiation pattern can be dynamically modified using different codes given to the FPGA (Figure 6). The simulated radiation pattern of beam scanning is obtained using this control mechanism [97]. In [25], the authors employed the on/off status of PIN diodes to alter the phase responses of meta-material elements.…”

“…As a result, the reflected radiation pattern can be dynamically modified using different codes given to the FPGA (Figure 6). The simulated radiation pattern of beam scanning is obtained using this control mechanism [97].…”