# An Overview of Signal Processing Techniques for RIS/IRS-aided Wireless Systems

arXiv: https://arxiv.org/abs/2112.05989 · HTML: https://mlsanity.com/paper/2112.05989/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Dec 2021.

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

- [Localization with Reconfigurable Intelligent Surface: An Active Sensing Approach](https://mlsanity.com/paper/2312.09002/) (2023)
- [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)
- [Design Optimization of NOMA Aided Multi-STAR-RIS for Indoor Environments: A Convex Approximation Imitated Reinforcement Learning Approach](https://mlsanity.com/paper/2406.13280/) (2024)
- [IRS-Enhanced Secure Semantic Communication Networks: Cross-Layer and Context-Awared Resource Allocation](https://mlsanity.com/paper/2411.01821/) (2024)
- [A Novel Deep Reinforcement Learning-based Approach for Enhancing Spectral Efficiency of IRS-assisted Wireless Systems](https://mlsanity.com/paper/2302.14706/) (2023)
- [Learning to Reflect: Hierarchical Multi-Agent Reinforcement Learning for CSI-Free mmWave Beam-Focusing](https://mlsanity.com/paper/2603.07370/) (2026)
- [Bypassing the CSI Bottleneck: MARL-Driven Spatial Control for Reflector Arrays](https://mlsanity.com/paper/2604.05162/) (2026)
- [Optimization Algorithms for Joint OFDM Waveform Design and RIS Configuration in 6G Networks: From Convex Relaxation to Foundation Models](https://mlsanity.com/paper/2606.31334/) (2026)

## Abstract (arXiv)

In the past as well as present wireless communication systems, the wireless propagation environment is regarded as an uncontrollable black box that impairs the received signal quality, and its negative impacts are compensated for by relying on the design of various sophisticated transmission/reception schemes. However, the improvements through applying such schemes operating at two endpoints (i.e., transmitter and receiver) only are limited even after five generations of wireless systems. Reconfigurable intelligent surface (RIS) or intelligent reflecting surface (IRS) have emerged as a new and revolutionary technology that can configure the wireless environment in a favorable manner by properly tuning the phase shifts of a large number of quasi passive and low-cost reflecting elements, thus standing out as a promising candidate technology for the next-/sixth-generation (6G) wireless system. However, to reap the performance benefits promised by RIS/IRS, efficient signal processing techniques are crucial, for a variety of purposes such as channel estimation, transmission design, radio localization, and so on. In this paper, we provide a comprehensive overview of recent advances on RIS/IRS-aided wireless systems from the signal processing perspective. We also highlight promising research directions that are worthy of investigation in the future.