[Paper Review] Active Reconfigurable Intelligent Surface Aided Wireless Communications

Ruizhe Long, Ying‐Chang Liang+2 more|arXiv (Cornell University)|Mar 1, 2021

Advanced Wireless Communication Technologies39 references18 citations

TL;DR

This paper proposes an active reconfigurable intelligent surface (RIS) that uses active loads (negative resistance) to reflect and amplify incident signals, overcoming the double-fading penalty of passive RIS. By jointly optimizing the reflecting coefficient matrix and receive beamforming via alternating optimization—using closed-form MMSE beamforming and sequential convex approximation—the system achieves higher spectral efficiency than passive RIS under the same power budget.

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.

Motivation & Objective

• Address the double-fading penalty in passive RIS-aided systems by introducing active RIS with signal amplification.
• Overcome the trade-off between enhancing desired signal power and amplifying RIS-correlated noise in active RIS systems.
• Design a joint optimization framework for reflecting coefficient matrix and receive beamforming to maximize spectral efficiency.
• Enable energy-efficient, high-capacity wireless communications using active RIS in SIMO systems.
• Provide a practical solution for active RIS deployment with power constraints and hardware limitations.

Proposed method

• Propose a novel active RIS architecture where each reflecting element (RE) incorporates active loads (negative resistance) to amplify incident signals instead of only reflecting them.
• Model the active RIS as a MIMO system with a reflecting coefficient matrix Φ and a noise model that includes RIS-correlated noise.
• Formulate a joint optimization problem to maximize the signal-to-interference-plus-noise ratio (SINR) at the receiver under total power and amplitude constraints.
• Apply alternating optimization: first solve for optimal receive beamforming w using closed-form linear MMSE, then optimize Φ via sequential convex approximation (SCA).
• Reformulate the Φ-optimization problem as a quadratic fractional program with convex constraints, enabling iterative SCA-based solution.
• Derive the optimal phase and amplitude for each RE in the unconstrained case, showing constructive combining and noise mitigation via channel gain balancing.

Experimental results

Research questions

• RQ1 How can active RIS with signal amplification improve spectral efficiency compared to passive RIS under the same power budget?
• RQ2 What is the optimal trade-off between desired signal enhancement and RIS-correlated noise amplification in active RIS systems?
• RQ3 How can the joint optimization of reflecting coefficients and receive beamforming be efficiently solved under practical hardware constraints?
• RQ4 What phase and amplitude control strategy maximizes the received SNR in an active RIS-aided SIMO system?
• RQ5 What are the fundamental performance limits of active RIS compared to passive RIS in a double-fading environment?

Key findings

• The proposed active RIS achieves higher spectral efficiency than passive RIS under the same total power budget due to signal amplification.
• The optimal reflecting coefficient for each RE is derived as φₘ* = (σ₁²|h₂ₘ|)/(σ₂²|h₁||gₘ|) × exp(j(arg(h₁) - arg(h₂ₘ) - arg(gₘ))), enabling constructive combining and noise mitigation.
• The maximum achievable SNR is γₛ* = (pₜ|h₁|²)/σ₁² + (pₜ‖h₂‖²)/σ₂², showing the benefit of amplification and channel gain balancing.
• The alternating optimization algorithm converges efficiently, with receive beamforming solved in closed-form using the MMSE criterion.
• The SCA-based optimization of the reflecting coefficient matrix effectively handles the non-convex fractional programming problem with power and amplitude constraints.
• Simulation results confirm that active RIS outperforms passive RIS in terms of spectral efficiency, especially in high-pathloss or low-SNR scenarios.