CTTC Sustainability Working Group

In CTTC we are committed to designing the next generation technologies in a sustainable manner to mitigate as much as possible the effects of climate change and to provide the most advanced tools for adaptation.  

Our research on sustainability directly involves a comprehensive set of communication technologies ranging from sensors, to wireless and wired networks, as well as satellites. Leveraging on in-house long-term expertise covering the full spectrum of telecommunication technologies (from physical layer access and devices to network layer services, protocols, and orchestration), complemented with the strong group in remote sensing and geomatics, CTTC is very well positioned to pursue a holistic approach for the challenging climate change problem.  

Some of the examples of the sustainable technologies we are addressing are in the fields of  

• Printed electronics with eco-friendly materials,  
• Energy-efficient hardware design,  
• Joint communication and sensing for a circular paradigm,  
• Radio access network energy monitoring and optimization,  
• Energy monitoring and optimization specifically catered to the different network segments (mobile networks, optical transport networks, satellite networks) and computing components (datacenters).  
• Distributed AI models (federated and decentralized) and lightweight machine learning models with brain-inspired and physics-informed solutions 
• Satellite remote sensing, Ground-based sensing, and its integration with the ICT networks. 

Knowledge advancement and technology development are carried out in close interactions with verticals and applications. To cite a few: Internet of Things, Artificial Intelligence of Things, Smart buildings, Smart cities, Smart grids, Mining, Landslide, Glacier/snow monitoring, Biomass estimation, Soil moisture estimation, Coastal monitoring, and Urban monitoring. 

For more information, visit the CTTC website:

As an example of the specific contributions, we list only a few of the technical contributions

Sustainable AI/ML 

Lightweight brain-inspired ML models have been considered to enable easier deployment of Reservoir Computing solutions, which establish the grounds for research solutions that compete with state-of-the-art AI deployed applications and for its deployment in real-world settings and resource-constrained devices. Hyperparameters optimization was identified as a major bottleneck in Reservoir Computing adoption, and we proposed an adaptive ϵ-greedy search strategy to significantly reduce the time and energy costs associated with offline tuning. An example of our work on Reservoir Computing can be found here.

Technology components  

Development of energy-aware technology building blocks for radio access: 

• Within the new open-source O-RAN paradigm, we looked at energy-proportional radio micro-orchestration solutions to develop a framework for optimizing power consumption at the digital and analog radio functions. This work leverages expertise in system-on-chip FPGA prototyping for 5G radio and power amplifier digital pre-distortion techniques.  
• Continue to develop signal processing and lower-layer solutions aimed at reducing power consumption: these efforts include emerging light Medium Access Control (MAC) protocols that reduce signaling overhead and focus on energy-efficient AI/ML algorithms; efficient designs for large and distributed multi-user and multi-antenna systems and distributed computing. 
• Development of Kubernetes simplified with AI-powered automatic scaling to optimize cloud resources/performance trade-off, reducing unnecessary resource consumption and the subsequent carbon emissions. Further implementation of collection mechanisms for energy measurements (from physical devices, virtual functions, and computing resources) is ongoing.  
• Development of power consumption models for optical transport infrastructure, combining optical transponders, optical switches, optical amplifiers, and AI-assisted SDN controllers.  
• Design of sensors for physical and chemical sensing (pressure, temperature, gas) using 6G network signals with applications in climate monitoring and industrial security. For example, we demonstrated multifunctional hardware like microwave cable with palladium for hydrogen and CO2 detection. 

Network architecture and services  

Projects such as SEASON and 6G-RAISING are examples of activities addressing sustainability from a network architecture and operation point of view. The first one is developing power-efficient Digital Signal Processing (DSP), and multiband SDM optical switching (MBoverSDM) to reduce the number of optical/electrical/optical (O/E/O) conversions by allowing traffic aggregation/router bypassing, and converged packet-optical solutions. The second is developing micro-orchestration services for edge-assisted energy-efficient transceivers that allow the reconfiguration of key low-PHY functions, such as the digital predistortion, and other 6G radio transceivers components with the use of AI/ML techniques. 

CTTC technologies at service of Earth & climate monitoring 

Leveraging on CTTC’s multidisciplinary research team a new internal working group started to develop a holistic approach towards enabling technologies for carbon credit measuring and offsetting exchanges. Integrating remote sensing satellite data, sensor data, and ICT network infrastructure with AI algorithms for prediction and anomaly detection, we are developing enhanced tools for CO2 measuring and CO2 offsetting tools.        

The opinions expressed on this blog are the opinions of the collaborators and do not necessarily represent the institutional opinion or positioning of CTTC.