Overview
An intelligent beam management solution that cuts training overhead and boosts energy efficiency in RIS‑assisted mmWave networks, supporting sustainable 6G rollouts.
Our result
This Key Exploitable Result delivers a functional, adaptive beamforming model for Reconfigurable Intelligent Surface (RIS)‑assisted mmWave networks, integrating position information (PI) with an online multi‑armed bandit (MAB) learning strategy and multi‑level codebook refinement. The resulting algorithm enables near‑optimal beam selection with drastically reduced overhead, offering a practical and energy‑efficient solution for high‑frequency 6G deployments.
Needs and target audiences
Technologies and methodologies are needed to enhance imec’s networked systems portfolio. The project will deliver Network Digital Twins (NDTs) to generate high-fidelity data for accurate beamforming models. It will also modernize University of Antwerp courses by integrating RIS, mmWave, and Digital Twin concepts, preparing students for 6G R&D. Results will be disseminated via journals and conferences, strengthening imec’s solutions in Connected Compute and Telecommunications and fostering academic–industry collaboration.
Current stage
The current stage is at a validated research prototype, supported by extensive simulation results in a realistic 3GPP‑based RIS‑mmWave environment. The adaptive PI‑guided multi‑level MAB beamforming model has been functionally demonstrated and benchmarked against state‑of‑the‑art baselines. The next steps are to evaluate the developed beamforming solution using mmWave RIS-equiped lab testbed
Unique value proposition
A lightweight, energy‑efficient beam management solution for RIS‑assisted mmWave networks that delivers near‑optimal performance with over 200× less training, strong robustness to location errors, and seamless integration with NDT
Keywords
- federated simulation
- ai-native architecture
- network digital twin
- network planning
- management and control
Research project acronyms
- 6G-TWIN
Research projects
- Integrating Network Digital Twinning into Future AI-based 6G Systems
Project identifiers
- 101136314
Contributors
- INTERUNIVERSITAIR MICRO-ELECTRONICA CENTRUM
Source: Horizon Results Platform