Active RIS vs. Passive RIS: Which Will Prevail in 6G? (2103.15154v8)

Abstract: As a revolutionary paradigm for controlling wireless channels, reconfigurable intelligent surfaces (RISs) have emerged as a candidate technology for future 6G networks. However, due to the "multiplicative fading" effect, the existing passive RISs only achieve limited capacity gains in many scenarios with strong direct links. In this paper, the concept of active RISs is proposed to overcome this fundamental limitation. Unlike passive RISs that reflect signals without amplification, active RISs can amplify the reflected signals via amplifiers integrated into their elements. To characterize the signal amplification and incorporate the noise introduced by the active components, we develop and verify the signal model of active RISs through the experimental measurements based on a fabricated active RIS element. Based on the verified signal model, we further analyze the asymptotic performance of active RISs to reveal the substantial capacity gain they provide for wireless communications. Finally, we formulate the sum-rate maximization problem for an active RIS aided multi-user multiple-input single-output (MU-MISO) system and a joint transmit beamforming and reflect precoding scheme is proposed to solve this problem. Simulation results show that, in a typical wireless system, passive RISs can realize only a limited sum-rate gain of 22%, while active RISs can achieve a significant sum-rate gain of 130%, thus overcoming the "multiplicative fading" effect.

• The paper demonstrates that active RIS significantly mitigates multiplicative fading, achieving a 130% capacity gain over passive RIS in realistic 6G scenarios.
• The paper introduces and validates an active RIS signal model through experimental measurements of noise and signal amplification.
• The paper highlights how active RIS offers practical SNR advantages over passive configurations, enhancing wireless performance even with strong direct links.

An Analysis of Active vs. Passive Reconfigurable Intelligent Surfaces in 6G Networks

The paper "Active RIS vs. Passive RIS: Which Will Prevail in 6G?" presents a comprehensive exploration of reconfigurable intelligent surfaces (RIS) technology, focusing on the comparative advantages and limitations of active and passive RIS configurations in the context of 6G networks.

Overview

RIS technology represents a key advancement for future wireless communication networks, particularly 6G. These surfaces allow for the control and manipulation of wireless channels to enhance communication performance. The paper identifies a critical issue with traditional passive RIS—limited capacity gains in scenarios where direct communication links are robust, primarily due to the "multiplicative fading" effect. This effect results from the compounded path losses of the transmitter-RIS-receiver link, necessitating the deployment of a large number of passive elements to achieve significant performance gains.

Active Reconfigurable Intelligent Surfaces

To address these limitations, the paper introduces the concept of active RIS. Unlike passive RIS, which simply reflect incoming signals, active RIS can amplify these signals using integrated reflection-type amplifiers. This key feature allows active RIS to compensate for the substantial path loss associated with the reflected links, thereby overcoming the "multiplicative fading" effect. The authors construct a signal model for active RIS and validate it through experimental measurements of noise and signal amplification characteristics of a fabricated active RIS element.

Numerical Analysis and Results

Numerical analysis demonstrates that active RIS can provide a substantial capacity enhancement over passive RIS. In particular, simulations show active RIS achieving sum-rate gains of approximately 130% in typical wireless configurations, compared to a mere 22% improvement with passive RIS. This performance is achieved even in scenarios with strong direct links, underscoring the capability of active RIS to mitigate the limitations encountered by passive configurations.

Theoretical Implications

From a theoretical standpoint, the distinction between the SNR scaling of passive (proportional to $N^2$, where $N$ is the number of RIS elements) and active RIS (proportional to $N$) is notable. Despite the seemingly greater SNR promise from passive RIS, active RIS tend to outperform in practical setups due to lower denominator terms in their SNR expressions—terms often multiplied by small constants and noise power parameters leading to practically stronger signal gain.

Future Directions

The paper calls for future exploration into various aspects of active RIS technology, including its hardware design, energy efficiency, channel estimation, and integration into existing network infrastructures. Given the promise shown by active RIS, particularly concerning power efficiency and achievable capacity gains, further research in these directions could expedite the adoption of RIS in 6G networks.

Conclusion

Overall, the paper provides valuable insights into the comparative potential of active and passive RIS within advanced communication systems. By addressing the fundamental constraints of passive RIS and proposing a novel active RIS model, the paper lays a foundation for enhanced wireless communication capabilities suited for the demands of future 6G networks. The detailed experimental validation and model verification presented pave the way for the continued development and optimization of RIS technologies.