The target outcomes address:

• Methods for an efficient effective, affordable, and accessible use of frequency spectrum for joint communication and sensing built upon energy efficient radio solutions by meeting 6G technical KPIs.
• Optimized radio physical layer solutions increasing availability empowered by machine learning under varying, dynamic and/or unknown channel conditions. Machine learning should adapt physical layer approaches and parameters for best exploitation of the radio channel capacity.
• Development of algorithms and energy efficient implementations for massive MIMO systems to increase radio channel capacity, coverage improvements under difficult propagation conditions and very high accuracy in location and positioning.
• Further innovative 6G RAN design by combining different physical layer functionalities and antenna concepts to meet challenging 6G technical requirements towards extremely high-throughput/low latency, sustainable and computationally-affordable implementation of radio systems.
• 6G spectrum candidate bands characterisations and co-existence/sharing technologies and approaches with other systems.
• Combination of different frequency bands depending on the requirements of the applications (throughput, latency, radio range …) and spectrum availability for optimum usage of the frequency spectrum and the minimisation of EMF effects.
• Algorithms, software and hardware implementations where appropriate, which can be used for PoC and later trials systems.
• Dissemination of solutions for international consensus building, which can be exploited in standardisation activities.
• Contributions to international standardisation.

Please refer to the "Specific Challenges and Objectives" section for Stream B in the Work Programme, available under ‘Topic Conditions and Documents - Additional Documents’.

The focus of this Strand is on several complementary issues mentioned below and applicants may select one or more of these issues. Topics can be proposed for any existing and potential future frequency band.

• Novel techniques for integrated sensing and communication to maximise the efficiency of spectrum usage and minimise resources (hardware, energy consumption) including accurate location and positioning. This topic may potentially include integrated waveform design (i.e. same waveform for both sensing and communication), integrated baseband and hardware design (front-ends, antenna systems and digital back-end), sensing algorithms, multi-band sensing technology cooperation, fusion with other sensing technologies, computing power, etc. Advanced self-interference cancellation techniques for further increase of spectral efficiency and enhanced antenna beam management for environmental sensing will also be included.
• Machine learning empowered physical layer evolutions to enrich/complement conventional model-based physical layer optimisation. This includes the development of end-to-end vs. block-based AI/ML-based transmitter/receiver chains along with the analysis of inherent trade-offs, channel learning and prediction; learnt signal constellation, modulation types, and channel (de)coding schemes; pre-coder optimization under non-ideal or unknown channel conditions, adoption of AI/ML in multi-antenna systems, in-radio network AI computing via e.g., over-the-air/coded computing, as well as semantic-oriented communications and protocol learning. It is also in scope the use of AI/ML to compensate for the losses caused by non-linear effects and other hardware impairments, or to address performance vs. resource/energy consumption trade-offs in resource-constrained network elements or devices.
• Cell-free and extreme exploitation of MIMO technologies potentially including reconfigurable surfaces considering but not limited to topics related to channel modelling of ultra-massive MIMO; feeding and control of each antenna element in addition to channel prediction; real-time estimation and feedback of a large number of channel elements; space-time-frequency coding to exploit all diversities; solutions that can control electromagnetic exposure for the above mentioned ultra-massive MIMO systems; centralized and distributed algorithms for coordinated transmission/reception encompassing a very large/massive number of antennas and/or users and possibly including MIMO predistortion for wideband massive arrays; solutions leveraging on the availability of large antenna deployments to achieve extreme accuracy in positioning,
• Key functionalities and technologies for 6G RAN system design, including any of the following topics: new (adaptive) waveform designs, novel random and multiple access schemes, advanced synchronisation and channel estimation strategies, in-band full duplex transceivers including self-interference cancelation; enhanced non-orthogonal multiple-access schemes (e.g., NOMA, RSMA) possibly in combination with multi-antenna processing; enhanced modulation and channel coding approaches towards error-free, extremely high-throughput/low latency, sustainable and computationally-affordable implementation of radio systems.
• Seamless integration of multiple frequency bands: reuse of existing frequency bands via dynamic spectrum sharing between existing systems and forthcoming 6G systems and access to new frequency bands. The scope also includes the optimum access to frequency bands depending on the radio environment and service requirements including spectrum sharing and load balancing. Several bands could be used simultaneously. EMF issues should be addressed. The spectrum efficient framework may include unlicensed bands and potentially optical access. Open and disaggregated solutions may be also considered for this topic. The work includes a review and analysis of the 6G candidate bands (European focus), of their characteristics in terms of spectrum co-existence needs with other radio systems and the associated intelligent sharing technologies that may be needed.

The scope includes, where relevant, harmonisation/coordination with Member States or Associated countries 6G initiatives. Any produced PoCs should be implemented in a way that their integration in SNS WP2025-26 Stream C and/or Stream D project will be possible (e.g., open-source solutions, appropriate documentation, support after the completion of the project).