In SOFIA, technical objectives beyond previous project IRENE for PHY layer are: i) integrating sensing and communications for Cell-Free massive MIMO (CF-mMIMO) ii) rely on ISAC for improving reliability and robustness in Visible Light Communications (VLC) scenarios, iii) include Artificial Intelligence (AI) techniques to reduce complexity, increase energy efficiency and flexibility and iv) novel designs of advance reconfigurable antennas. Regarding satellite communication, SOFIA’s technical objectives beyond IRENE encompass: i) challenge Release 17 assumptions and exert an influence on future releases with a focus on satellite deployments above 10 GHz. ii) develop diverse techniques for the efficient implementation of Orthogonal Time Frequency Space (OTFS) in Non-Geostationary Earth Orbit (NGEO) systems. iii) investigate handover mechanisms and explore beam management solutions. iv) analyze and enhance swarm satellite architecture and v) design an efficient Radio Intelligent Controller (RIC) based on AI and intelligent and adaptive beamforming. SOFIA also focuses on the development of efficient Integrated Sensing and Communications (ISAC) schemes crucial for satellite network deployment and the improvement of mmWave systems. Furthermore, SOFIA addresses the significant area of 6G antenna development and explores the novel domain of Integrated Optical Sensing and Communications (IOSAC). In relation to the RRM, SOFIA will explore new avenues not considered in IRENE, in particular: i) the concept of resource is generalized to encompass not only radio resources (i.e. spectrum), but also infrastructure and, therefore schemes will be derived to combine different infrastructure elements (ultradense segments, cellular, NGEO) jointly with multiband frequency resources to satisfy different QoS requirements ii) radio and/or infrastructure resources will need to be managed to provide communication and sensing capabilities and iii) in order to support the eclectic mix of applications foreseen in 6G, a higher level of resource management in the form of slice definition or creation of multicasting groups will be explored.

• Satellite communications: Ensuring coverage in remote and underserved regions is crucial, but equally important is providing the necessary offloading capabilities and resilience to link failures in densely populated areas. SOFIA aims to enhance the performance of both GEO and NGEO satellites through the development of various techniques. SOFIA covers aspects such as air-interface, beam management, waveforms, handovers, resource management, and adaptive beamforming. Additionally, SOFIA will explore systems involving cooperative satellite swarms, delving into ISAC and joint communication-computing strategies.
• Massive MIMO and cell-free architectures: Massive MIMO is crucial technology to achieve the required efficiency against the increasing data traffic demand. On one hand, SOFIA will investigate the non-coherent massive MIMO and/or new waveforms to deal with the fast-varying or low channel knowledge scenarios. On the other hand, significant effort will be dedicated to overcoming the challenges imposed by the adoption of the CF-mMIMO architecture considering that it is a promising solution for a future sustainable network.
• Integrate sensing and communications (ISAC): SOFIA will design an efficient use of resources for integrating the sensing capabilities and communications to enhance communications thanks to extra information on sensing and improve the current localization systems with communications capabilities.
• High frequencies and 6G Antennas: SOFIA will investigate diverse technological solutions aimed at delivering cost-effective and power-efficient 6G antennas. SOFIA solutions will be designed to facilitate directional transmissions in frequencies above 6GHz, introduce new capabilities like integrated sensing, and ensure that antennas do not pose obstacles to accessing 6G services. Several signal processing schemes will be developed to enhance the use of these frequency bands.
• Slicing: SOFIA will develop slicing resource management solutions to deal with the multi-service environment in 6G networks with special focus on the application in CF-mMIMO context. Joint-communication-sensing will be considered to reduce the latency and accelerate data collection. Moreover, a physical layer design appropriate for slicing will be considered (PHY-RAN slicing). Additionally, graph signal processing techniques will be exploited to deal with the optimization of multi-connectivity in hybrid terrestrial-satellite networks.
• Optical communications: VLC are an alternative for RF communication in places where RF is not viable. SOFIA will consider developing techniques to improve optical communication performance and improve its combination with RF communications. SOFIA will also target developing IOSAC schemes to enable the use of optical hardware for multiple purposes.
• AI: AI techniques play a pivotal role in the development of future networks to deal with automation and optimization in complex scenarios where the theoretical model is not available or is intractable. SOFIA will develop AI-based solutions to provide the 4D network: with the necessary intelligence, with adaptive and flexible optimization tools, and with predictive configurability. Special focus will be given to distribute federated learning-based solutions.

A common thread for the different techniques that will be developed in SOFIA will be energy efficiency and reliability since this can be considered as one of the main enablers for the reduction of both the carbon footprint of communication systems and the operational expenditure of the wireless network. The improvement of the energy efficiency along with providing global coverage, achieving distributed intelligence, and the support of different environments (such as limited/crowded connections, high speed trains, short-range systems, etc.) and services (such as eHealth applications, tactile internet, holographic teleportation. etc.) will contribute to the main goal of SOFIA in achieving sustainable and reliable communications.

FUNDING