Reconfigurable Intelligent Surfaces: A Signal Processing Perspective With Wireless Applications (2102.00742v2)

Abstract: Antenna array technology enables directional transmission and reception of wireless signals, for communications, localization, and sensing purposes. The signal processing algorithms that underpin this technology began to be developed several decades ago [1], but it is first with the ongoing deployment of the fifth-generation (5G) wireless mobile networks that it becomes a mainstream technology [2]. The number of antenna elements in the arrays of the 5G base stations and user devices can be measured at the order of 100 and 10, respectively. As the networks shift towards using higher frequency bands, more antennas fit into a given aperture. The 5G developments enhance the transmitter and receiver functionalities, but the wireless channel propagation remains an uncontrollable system. This is illustrated in Fig. 1(a) and its mathematical notation will be introduced later. Transmitted signals with three different frequencies are shown to illustrate the fact that attenuation can vary greatly across frequencies. Looking beyond 5G, the advent of electromagnetic components that can shape how they interact with wireless signals enables partial control of the propagation. A reconfigurable intelligent surface (RIS) is a two-dimensional surface of engineered material whose properties are reconfigurable rather than static [4]. This article provides a tutorial on the fundamental properties of the RIS technology from a signal processing perspective. It is meant as a complement to recent surveys of electromagnetic and hardware aspects [4], [7], [11], acoustics [12], communication theory [13], and localization [8]. We will provide the formulas and derivations that are required to understand and analyze RIS-aided systems using signal processing, and exemplify how they can be utilized for improved communication, localization, and sensing.

• The paper demonstrates how RIS improves wireless links by enabling SNR to scale quadratically with the number of elements under optimal conditions.
• It develops an end-to-end communication model for narrowband and wideband scenarios, showing how dynamic RIS tuning mitigates interference and Doppler effects.
• The study extends RIS applications to localization and sensing, improving signal observability and reducing hardware constraints in dynamic environments.

Reconfigurable Intelligent Surfaces: A Signal Processing Perspective With Wireless Applications

The paper presents a comprehensive analysis of Reconfigurable Intelligent Surfaces (RIS) in wireless communications from a signal processing viewpoint. As part of the transformative technologies considered for beyond 5G and future wireless networks, RIS acts as a revolutionary means to control electromagnetic wave propagation. Such surfaces, essentially composed of engineered materials, can be strategically designed to integrate with wireless communication systems, providing new pathways for signal processing and enhancing wireless link performance.

Overview and System Model

The paper introduces RIS as a tool to modulate the wireless propagation environment by reconfiguring electromagnetic interactions. Unlike conventional passive reflectors, RIS units are capable of dynamically tuning the amplitude, phase, and polarization of incident waves. Theoretical models in the article demonstrate how RIS can provide additional paths for wave propagation, enhancing signal-to-noise ratio (SNR), mitigating channel fading, and addressing interference.

The authors develop an end-to-end communication system model involving RIS, encompassing narrowband and wideband scenarios. This model encapsulates the interactions between the signal emitted by the transmitter and the RIS, detailing how it reaches the intended receiver. By understanding the interaction of these channels through pseudo-baseband representations, researchers can leverage this framework to design systems that harness RIS to improve channel quality.

Capacity Analysis and Optimization

The paper explores optimizing RIS configurations to maximize the communication capacity of the wireless channel. It proposes configurations for narrowband scenarios that ensure constructive interference of signals reaching the receiver. The paper reveals that RIS utilization results in an SNR that scales with the square of the number of RIS elements under optimal conditions. This quadratic scaling is notable when contrasted with the linear scaling associated with beamforming in traditional antenna arrays.

For wideband systems, the optimization problem expands due to the frequency-selective nature of the channel, requiring careful power allocation and subcarrier optimization. The paper leverages strategies such as strongest tap maximization (STM) to navigate this complexity, providing a tractable approach to deal with multi-carrier signals in RIS-aided environments.

Mobility and Doppler Effect Considerations

Addressing time-varying channels caused by user mobility, the research adapts the RIS configuration to mitigate Doppler effects, proposing a linear time-variant (LTV) system viewpoint. It illustrates how RIS can electronically synthesize motion to counteract Doppler shifts, reduce intersymbol interference, and improve signal alignment in dynamic environments. This flexibility positions RIS as a potent tool for maintaining robust communications in scenarios with significant user mobility.

Localization and Sensing

Beyond communication enhancement, RIS facilitates improved localization and sensing capabilities. By introducing new geometric measurements through RIS-aided angles and delays, the infrastructure requirement for effective localization reduces substantially. Integrating RIS in scenarios with limited direct line-of-sight paths enhances signal observability, crucial for both indoor and outdoor applications. The channel parameter estimation, crucial for localization, becomes possible with a structured framework of RIS configurations.

Future Prospects and Implications

The theoretical exploration sets the stage for future development concerning practical RIS implementations, focusing on empirical validation and refined electromagnetic models. Incorporating mutual coupling effects and non-linear system responses into RIS deployment could push the boundaries of RIS design further. These challenges and opportunities remain open fields for advancing communication theory, signal processing algorithms, and system integrations.

As researchers contemplate RIS integration into the standard protocol stacks, the potential of creating "smart radio environments" looms large, with impacts stretching into various AI-driven wireless technologies. The paper argues strongly for investigating system-level interactions and hardware-software co-designs to unlock the full potential of RIS.

In conclusion, this paper offers a foundational perspective on RIS technology, situating it firmly in the evolving landscape of wireless communication and signal processing. By combining rigorous theoretical analysis with feasible computational strategies, it suggests an actionable path forward for researchers and practitioners looking to harmonize RIS technology within next-generation wireless networks.