Knowledge and technology transfer
Impact and knowledge transfer
Impact of the project results
Scientific-technical, economic and social impact derived from the project, the sectors on which the results will have an effect, and the activities carried out that may lead to knowledge transfer.
Advance of knowledge within the project's field
The project has advanced the state of the art in energy-efficient mobile networks by introducing the Hypercell concept, a novel paradigm for cellular energy saving that, to the best of our knowledge, had not been previously formulated in this form. Current energy-saving solutions are limited by the need to keep terrestrial coverage cells permanently active to guarantee blanket coverage. ZZNets has addressed this limitation by proposing that an aerial, elevated or non-terrestrial layer assumes this blanket-coverage role during low-traffic periods, enabling terrestrial cells to be dynamically switched off while preserving service continuity.
This represents a conceptual advance towards the vision of zero-bit, zero-watt cellular networks and green 3D cellular networks, where cells that do not carry useful traffic can be placed in deep sleep without compromising coverage. The project has focused on implementing the Hypercell concept using HAPS and UAV-based platforms, while also showing that the same principle can be realized with other emerging non-terrestrial network technologies, such as satellites. This increases the scientific and technological relevance of the concept, as it connects energy-efficient cellular operation with the growing field of integrated terrestrial/non-terrestrial networks.
The Hypercell paradigm
A new way of reducing network energy consumption by transferring the blanket-coverage role from terrestrial cells to an aerial, elevated or non-terrestrial layer, allowing deep sleep of many terrestrial cells during low-traffic periods without loss of service continuity.
Fundamental mechanisms for network operation
Dynamic Hypercell–terrestrial-cell pairing, distributed carrier shutdown and wake-up procedures, traffic-aware decision support, SINR prediction and power-consumption model exchange — all disseminated through scientific publications and open research outputs so the community can reuse and extend them.
AI-based modelling and digital-twin framework
Practical SINR predictors based on standardised 5G reference-signal measurements, generative-AI channel models that accelerate large-scale simulation while preserving spatial consistency, and data-driven traffic forecasting from operational network data — together with the Giulia system-level simulator and the Dedalo interface.
Overall, ZZNets has generated new scientific knowledge at the intersection of green mobile networks, non-terrestrial networks, artificial intelligence, digital twins and network optimisation. The main advance is not merely a collection of individual algorithms, but a new framework for understanding how future mobile networks can use aerial or non-terrestrial coverage layers, AI-based modelling and digital-twin-assisted optimisation to substantially reduce energy consumption.
Socio-economic impact of the project results
The project addresses one of the main challenges of current and future mobile networks: reducing energy consumption while maintaining reliable connectivity. Mobile networks are essential digital infrastructure for society, industry and public services, but their energy demand is expected to grow with 5G-Advanced and 6G deployments. By proposing the Hypercell concept and its associated AI-based energy-saving mechanisms, ZZNets contributes to more sustainable, cost-efficient and environmentally responsible mobile networks.
Environmental sustainability
Lower electricity consumption across the radio access network. By providing an alternative blanket-coverage layer, the Hypercell approach enables deeper sleep modes for terrestrial cells during low-traffic periods, helping to lower the carbon footprint of telecommunications infrastructure.
Economic competitiveness
Reduced operational expenditure for mobile network operators and new optimisation tools for the sector. The results are relevant for operators, telecom equipment vendors, drone-based communication providers and future non-terrestrial network platforms.
Social benefit and resilience
More flexible and resilient connectivity. Aerial or non-terrestrial coverage layers can support communications in temporary, emergency or hard-to-cover scenarios, and the experimental platform demonstrates the feasibility of commercial 5G equipment on tethered aerial platforms — with applications in public safety, emergency response, smart cities and aerial corridors.
Human-capital development
Recruitment and training of highly qualified personnel — doctoral researchers and technical staff specialised in artificial intelligence, wireless communications, digital twins and experimental 5G platforms — strengthening the research and innovation capacity of UPV-iTEAM.
Dissemination activities have targeted both the scientific community and relevant industrial stakeholders, through high-impact journal and conference publications, invited talks, tutorials, international workshops, open-source tools, and collaborations with universities and companies. In particular, the project contributed to the organisation of a workshop on the integration of terrestrial and non-terrestrial networks, where the Hypercell concept and related results were presented to academic and industrial participants.
Collaborations with entities or companies able to exploit the results, and exploitation plan
Yes. The project has maintained a close collaboration with Huawei Technologies, the main industrial partner of ZZNets, given its strategic interest in energy-efficient mobile networks, AI-based network modelling, digital twins and future 5G-Advanced/6G architectures.
Huawei researchers contributed industrial expertise on radio access network energy efficiency, carrier shutdown, power-consumption modelling, digital-twin-based network evaluation and AI-based modelling. This collaboration helped align the research with realistic deployment requirements and with the needs of future commercial mobile networks.
The results with potential industrial exploitation include the Hypercell concept, the associated carrier-shutdown and wake-up mechanisms, the use of AI models for traffic-aware and energy-aware decisions, the digital-twin simulation framework, and the generative-AI channel modelling tools developed during the project. These may be exploited as part of future network-planning, network-optimisation and energy-saving tools for 5G-Advanced and 6G radio access networks.
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Short term
Further development of the project outcomes through joint scientific publications, open-source simulation tools and industrial research collaboration with Huawei.
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Medium term
Transfer of the most mature results — especially the Hypercell concept, the AI-enabled digital twin and the energy-saving mechanisms — towards standardisation-oriented studies and future product differentiation in network-management and optimisation tools.
Project activities that may generate valorisation and knowledge transfer
Several activities developed in ZZNets may generate valorisation and knowledge transfer due to their applicability to future energy-efficient 5G-Advanced and 6G networks.
Hypercell architecture and carrier-shutdown protocol
A new approach to reducing network energy consumption by transferring the blanket-coverage role from terrestrial cells to an aerial, elevated or non-terrestrial layer. The associated mechanisms for cell pairing, distributed shutdown, wake-up and information exchange may be further developed into future network-management and energy-saving solutions.
Hypercell experimental platform
An experimental platform built and validated on commercial 5G equipment, a private 5G network and a tethered aerial platform. It can support future demonstrations, pilot experiments, industrial validation and collaborative projects with companies interested in aerial base stations, resilient communications and non-terrestrial networks.
AI-enabled network digital twin
The Giulia system-level simulator, the Dedalo interface, the automated scenario-generation pipelines and the 3D visualisation environment provide a realistic platform to evaluate energy-saving mechanisms, AI-based optimisation methods and future RAN architectures before deployment — supporting both academic research and industrial pre-validation.
AI-based modelling components
Traffic forecasting models based on operational network data, SINR predictors based on standardised 5G measurements, power-consumption model exchange mechanisms and generative-AI channel models. These can be reused in future AI-native network management systems and digital-twin-based optimisation tools.
Open-source tools, publications and training
Open-source tools, scientific publications, doctoral training and industrial collaboration facilitate the dissemination and reuse of the project results, strengthen UPV-iTEAM's position in green 5G/6G research, and provide a basis for future technology-transfer activities with Huawei and other stakeholders in the telecommunications sector.