# Active RIS vs. Passive RIS: Which Will Prevail in 6G?

arXiv: https://arxiv.org/abs/2103.15154 · HTML: https://mlsanity.com/paper/2103.15154/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Mar 2021.

## Built on by (most cited first, 8 of 8)

- [Multi-Functional RIS-Enabled in SAGIN for IoT: A Hybrid Deep Reinforcement Learning Approach with Compressed Twin-Models](https://mlsanity.com/paper/2507.16204/) (2025)
- [Parametrized Sharing for Multi-Agent Hybrid DRL for Multiple Multi-Functional RISs-Aided Downlink NOMA Networks](https://mlsanity.com/paper/2601.00538/) (2026)
- [Active RIS-aided EH-NOMA Networks: A Deep Reinforcement Learning Approach](https://mlsanity.com/paper/2304.12184/) (2023)
- [QoS Improvement in Multi User Cellular-Symbiotic Radio Network Assisted by Active-STAR-RIS](https://mlsanity.com/paper/2401.08301/) (2024)
- [Multi-stream Transmission for Directional Modulation Network via Distributed Multi-UAV-aided Multi-active-IRS](https://mlsanity.com/paper/2404.15297/) (2024)
- [Neural Channel Knowledge Map Assisted Scheduling Optimization of Active IRSs in Multi-User Systems](https://mlsanity.com/paper/2508.07009/) (2025)
- [Beyond-Diagonal RIS Under Non-Idealities: Learning-Based Architecture Discovery and Optimization](https://mlsanity.com/paper/2510.15701/) (2025)
- [Learning to Reflect: Hierarchical Multi-Agent Reinforcement Learning for CSI-Free mmWave Beam-Focusing](https://mlsanity.com/paper/2603.07370/) (2026)

## Abstract (arXiv)

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.