Project supported under ECIU Seed Programme.
Implementation period: 2026-03-01 - 2028-02-28
Project coordinator:
Kaunas University of Technology
Project partners:
University of Aveiro
Lodz University of Technology
Dublin City University
Overview:
The EAREC project addresses a joint framework for energy-aware and resilient communications operating at the network edge. We combine deep learning (DL)-based physical-layer (PHY) intelligence with dynamic, network-level energy management. By doing so, the project creates a closed-loop optimization system that significantly improves receiver performance and the reliability of Internet of Things (IoT) applications—ranging from vehicular networks to industrial IoT and smart grids.
Our Objectives:
Our primary ambition is to establish a strong scientific and methodological foundation for future joint proposals under the Horizon Europe framework, focusing on next-generation intelligent and sustainable 6G systems. The work focuses on:
- Low-power DL-based channel estimation: Developing algorithms that improve signal robustness and communication quality under low signal-to-noise ratio (SNR) and high-interference conditions.
- Energy-aware controller placement: Creating models that dynamically allocate computational and control tasks across edge nodes to optimize energy consumption.
- Cross-layer intelligence: Integrating information from physical, link, and network layers to allow communication systems to adapt in real time to shifting environmental constraints.
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