Active Reconfigurable Intelligent Surface Aided Wireless Communications (2103.00709v1)

Abstract: Reconfigurable Intelligent Surface (RIS) is a promising solution to reconfigure the wireless environment in a controllable way. To compensate for the double-fading attenuation in the RIS-aided link, a large number of passive reflecting elements (REs) are conventionally deployed at the RIS, resulting in large surface size and considerable circuit power consumption. In this paper, we propose a new type of RIS, called active RIS, where each RE is assisted by active loads (negative resistance), that reflect and amplify the incident signal instead of only reflecting it with the adjustable phase shift as in the case of a passive RIS. Therefore, for a given power budget at the RIS, a strengthened RIS-aided link can be achieved by increasing the number of active REs as well as amplifying the incident signal. We consider the use of an active RIS to a single input multiple output (SIMO) system. {However, it would unintentionally amplify the RIS-correlated noise, and thus the proposed system has to balance the conflict between the received signal power maximization and the RIS-correlated noise minimization at the receiver. To achieve this goal, it has to optimize the reflecting coefficient matrix at the RIS and the receive beamforming at the receiver.} An alternating optimization algorithm is proposed to solve the problem. Specifically, the receive beamforming is obtained with a closed-form solution based on linear minimum-mean-square-error (MMSE) criterion, while the reflecting coefficient matrix is obtained by solving a series of sequential convex approximation (SCA) problems. Simulation results show that the proposed active RIS-aided system could achieve better performance over the conventional passive RIS-aided system with the same power budget.

• The paper demonstrates that active RIS using negative resistance amplify signals to mitigate double-fading losses compared to passive RIS.
• An alternating optimization method jointly optimizes receive beamforming (via MMSE) and reflect beamforming (using SCA) to maximize SNR.
• Numerical results confirm that active RIS achieve superior performance and energy efficiency, enabling compact and flexible wireless deployments.

Active Reconfigurable Intelligent Surface Aided Wireless Communications

In the paper titled "Active Reconfigurable Intelligent Surface Aided Wireless Communications," the authors introduce an innovative concept for wireless communication enhancement via active Reconfigurable Intelligent Surfaces (RIS). This paper explores how active RIS, as opposed to the traditional passive RIS, can significantly improve signal power by not only reflecting but also amplifying the incident signals through active loads comprising negative resistance elements. The paper positions active RIS as a key technology capable of overcoming the innate double-fading attenuation challenge observed in conventional RIS setups, which predominantly rely on passive reflecting elements (REs).

Summary and Analysis

The proposed active RIS paradigm replaces passive reflecting elements with active elements, which are essentially engineered using negative resistance technology such as tunnel diodes. This configuration permits the amplification of incident signals without necessitating complex RF chain components typically associated with such tasks. The core advantage of active RIS is their ability to enhance wireless links more aggressively and effectively compared to their passive counterparts, thereby making efficient use of the power budget allocated to the RIS. The paper highlights the enhanced spectrum and energy efficiency achievable with the active RIS approach, while leveraging a Single Input Multiple Output (SIMO) communication setup as a practical case paper.

The methodology employed in the paper involves formulating an optimization problem aimed at maximizing the received signal-to-noise ratio (SNR). This entails a joint optimization strategy involving receive beamforming at the receiver and reflect beamforming at the RIS. The RIS design aims to balance received signal power amplification against RIS-correlated noise minimization, a challenge inherent to the active RIS design due to the amplification of thermal noise in addition to the signal.

To tackle the aforementioned optimization problem, the authors propose an alternating optimization algorithm. The approach decomposes the problem into two stages: the receive beamforming, which is optimized using a closed-form solution based on the linear minimum-mean-square-error (MMSE) criterion; and the reflect beamforming, optimized via sequential convex approximation (SCA). This iterative method demonstrates convergence to a suboptimal solution that effectively leverages active RIS functionalities.

Numerical Results and Implications

The numerical results substantiate the thesis that active RIS can outperform passive RIS under equivalent power conditions, providing superior integration flexibility and performance in SNR-constrained environments. The paper discusses that active RIS achieves these gains by optimizing the number of active elements and the amplification power for a given power budget, thereby presenting an intriguing trade-off. Notably, the paper posits that the enhanced reflect beamforming capabilities allow active RIS systems to maintain performance advantages even under varying and potentially suboptimal deployment scenarios in terms of signal path distance and environmental fading conditions.

Moreover, the discussion includes a comparative analysis of the optimal deployment strategies for active versus passive RIS systems, shedding light on the practical considerations that would underpin real-world implementations. The results propose that actively amplifying REs lead to more compact and effective setups for spatially constrained deployments, offering a distinct advantage over traditional luminally extensive passive RIS installations.

Future Directions

While the current work propels RIS from merely reflective to active amplification roles, several avenues for future research are identified:

• Integration with multi-user and multi-channel communications networks, aiming to capitalize on RIS to optimize network-wide performance.
• Exploration of energy neutrality for active RIS, which would further enhance their deployment viability in diverse scenarios.
• Development of adaptive systems capable of dynamically switching between active and passive modes depending on environmental and operational metrics.
• Comprehensive comparison with alternative technologies like amplify-and-forward relays to delineate use-cases and hybridation scenarios.

In conclusion, this paper presents compelling evidence on the capabilities of active RIS in redefining and amplifying the wireless communication landscape. It forms a promising foundation for further research into scalable, efficient, and adaptable wireless infrastructure, potentially catalyzing a shift in how signal manipulation and transmission are conceptualized and executed in next-generation networks.