Reconfigurable Intelligent Surfaces: Potentials, Applications, and Challenges for 6G Wireless Networks (2107.05460v1)

Abstract: Reconfigurable intelligent surfaces (RISs), with the potential to realize a smart radio environment, have emerged as an energy-efficient and a cost-effective technology to support the services and demands foreseen for coming decades. By leveraging a large number of low-cost passive reflecting elements, RISs introduce a phase-shift in the impinging signal to create a favorable propagation channel between the transmitter and the receiver.~\textcolor{black}{In this article, we provide a tutorial overview of RISs for sixth-generation (6G) wireless networks. Specifically, we present a comprehensive discussion on performance gains that can be achieved by integrating RISs with emerging communication technologies. We address the practical implementation of RIS-assisted networks and expose the crucial challenges, including the RIS reconfiguration, deployment and size optimization, and channel estimation. Furthermore, we explore the integration of RIS and non-orthogonal multiple access (NOMA) under imperfect channel state information (CSI). Our numerical results illustrate the importance of better channel estimation in RIS-assisted networks and indicate the various factors that impact the size of RIS. Finally, we present promising future research directions for realizing RIS-assisted networks in 6G communication.

• The paper provides a thorough examination of reconfigurable intelligent surfaces (RIS) for 6G wireless networks, exploring their potential to create smart radio environments and address limitations of 5G.
• Integration of RIS with technologies like NOMA, SWIPT, UAVs, BackCom, mmWaves, and multi-antenna systems is discussed, highlighting gains in efficiency and coverage despite complexities.
• Key challenges for practical RIS implementation include efficient reconfiguration control, accurate channel estimation, and optimal deployment strategies to maximize performance gains effectively.

Reconfigurable Intelligent Surfaces: Potentials and Challenges for 6G Networks

The paper "Reconfigurable Intelligent Surfaces: Potentials, Applications, and Challenges for 6G Wireless Networks" presents a thorough examination of the emerging technology of reconfigurable intelligent surfaces (RISs) and their potential application in future wireless communication systems, specifically sixth-generation (6G) networks. The authors, Sarah Basharat et al., explore the integration of RIS with various communication technologies while highlighting the performance improvements and practical challenges involved.

The concept of RIS brings forth a paradigm shift in wireless communication by altering the propagation channel to create smart radio environments. RIS comprises numerous passive reflecting elements capable of inducing phase changes in impinging signals, thereby optimizing signal transmission from the base station (BS) to the receiver. This technology stands out as a cost-effective and energy-efficient solution to address the inadequacies faced by 5G networks, which include high hardware costs and signal vulnerability, and pave the way for smart wireless environments.

Integration of RIS with Emerging Technologies

Several notable integrations of RIS with existing communication paradigms are discussed:

1. RIS and NOMA (Non-Orthogonal Multiple Access): The RIS-enhanced NOMA system promises gains in spectral and energy efficiency for future networks. Although RIS facilitates coherent phase-shifting design to optimize beamforming, practical constraints such as system complexity and hardware limitations remain critical considerations.
2. RIS and SWIPT (Simultaneous Wireless Information and Power Transfer): RIS significantly enhances the energy efficiency of SWIPT systems by increasing signal strength at the endpoints through optimized reflections. Iterative optimization techniques maximize the weighted sum-rate, proving advantageous for practical applications.
3. RIS and UAVs (Unmanned Aerial Vehicles): RIS improves communication quality between UAVs and ground users by establishing virtual line-of-sight (LoS) channels, thus overcoming signal blockages prevalent in dense urban environments. Intelligent trajectory and beamforming optimization further amplifies these gains.
4. RIS and BackCom (Backscatter Communication): The limitations in BackCom's operational range can be addressed through RIS assistance, thereby enhancing detection performance and reducing power requirements using novel optimization frameworks and deep reinforcement learning approaches.
5. RIS and mmWaves (Millimeter-Wave): The integration of RIS with mmWave technology adapts to disruptions in communication links by introducing additional paths to maintain coverage and performance, optimizing beamforming under alternative strategies.
6. RIS and Multi-Antenna Systems: The use of RIS over conventional MISO (Multiple Input Single Output) systems promises improved quality of service and sum-rate performance with reduced hardware complexity. Discrete beamforming optimization algorithms further allow for practical, low-cost implementations.

Challenges and Practical Implementation

The deployment of RIS-assisted networks faces several challenges, including:

• RIS Reconfiguration: Achieving efficient signal reflections necessitates sophisticated control mechanisms for phase-shifts and amplitudes. Hardware and design complexities remain an enduring limitation, making the adaptation of discrete variables necessary.
• Channel Estimation: Accurate estimation of channels is crucial, yet challenging due to the RIS's large-scale architecture, signaling overhead, and the presence of channel estimation errors.
• Deployment Optimization: Strategic placement of RIS and determining appropriate sizes are crucial for maximizing performance gains while minimizing costs and accommodating user distributions.

Case Study and Research Directions

The paper presents a case paper of RIS-assisted NOMA networks, demonstrating the impact of channel estimation errors on spectral efficiency. Findings indicate that performance benefits can be leveraged effectively by deploying a higher number of RIS elements, which compensates for imperfections in CSI (Channel State Information).

Future research directions proposed by the authors include further exploration into RIS in terahertz (THz) communication, aerial RIS deployments, physical layer security enhancements, applications in optical wireless communication, and the integration of RIS in massive MIMO (mMIMO) networks.

Implications

The research in this paper highlights the transformative potential RIS holds for the next generation of wireless systems. Practical implications include increased reliability and coverage in urban environments, enhanced energy, and spectral efficiency, alongside reduced infrastructure costs. Theoretical implications revolve around expanding communication paradigms to include smarter environments, paving the way for substantial advances in network capabilities.

As the pursuit of RIS continues, these findings will serve as a crucial foundation for future innovations in wireless communications, acknowledging both its promise and the challenges to its implementation.