Wireless Communication Technologies and Signal Processing – Standardisation and Follow-up/PoCs -

Expected Outcome:

• Optimized physical layer solutions and methods for an efficient, affordable, and accessible use of frequency spectrum, able to meet 6G technical KPIs and KVIs.
• Development of algorithms for massive MIMO systems for increased channel capacity and coverage improvements under difficult propagation conditions.
• An AI-native framework for RAN networks based on AI/ML and semantic technologies.
• Technologies and approaches for co-existence/sharing with other communication systems.
• Mechanisms and strategies to underpin automation and disaggregation in the RAN segment.
• Integration of function accelerators at the 6G RAN/compute continuum, where required.
• Algorithms, software and hardware implementations that can be eventually used for PoC and trials systems.
• Contributions to international standardisation.

Sustainability (from environmental, economic and societal perspectives) might be regarded as a horizontal aspect to be addressed by the aforementioned priorities, wherever possible. Developing technologies that will maximize system and equipment lifetime, thanks to modular, evolutive and flexible design that unlock the ability to adapt to new services, support new capabilities and satisfy 6G performance requirements is a relevant outcome.

Objective:

Please refer to the "Specific Challenges and Objectives" section for Stream B-02 in the Work Programme, available under ‘Topic Conditions and Documents - Additional Documents’.

Scope:

The scope of this topic focuses on the following areas:

• Physical layer technologies for enhanced spectral efficiency which includes energy-efficient new waveform design (featuring e.g., low PAPR, low complexity processing), backwards compatibility with existing CP-OFDM waveforms, or self-synchronizing modulation and waveform. Modulation and coding aspects are also in scope, including source-channel codes for short packet transmission, coding and caching for over-the-air computing in the network edge, or energy-efficient implementation of key physical-layer algorithms such as FEC or channel estimation. Asynchronous non-orthogonal multiple access schemes (e.g., NOMA, RSMA), advanced interference cancellation, advanced (full) duplexing strategies, or UE relaying can be considered, as well. Where relevant, RAN coordination (e.g., multi-TRP), improved lower layer signalling in 6G Air Interface, or physical-layer security aspects can also be addressed.
• Extreme exploitation of MIMO technologies, this including advanced massive MIMO technologies and extremely large antenna arrays (XL-MIMO) for increased network capacity and spectral efficiency and/or enhanced indoor coverage/localization; holographic beamforming and novel beam management schemes in massive MIMO settings leveraging on hybrid analog-digital front-end architectures; scalable, robust and low-complexity/overhead CSI acquisition strategies; massively distributed and cell-free MIMO technologies and architectures for improved coverage, reliability and mobility support and related synchronization, calibration and coordination aspects.
• AI/ML & semantic communications targeted at providing a native AI framework for RAN networks by using AI/ML for the lower layers of the protocol stack (e.g., including PHY, MAC and resource optimization), including AI-assisted multi-user and massive-MIMO systems channel coding aspects, the reduction of power consumption in the RAN or multi-modal model training (e.g., vision-assisted) for improved radio/network efficiency. Protocol learning, automated generation of lean, customizable neural radio protocol stacks, and learning networks, as well as related aspects such as distributed and centralized learning trade-offs, or conflict and anomaly detection and resolution are also in scope. This focus area notably includes semantic communications, or trustworthy/safe/explainable AI and the exploitation of generative AI for RAN optimization.
• Spectrum sharing and RAN co-existence focuses on aspects such as dynamic spectrum sharing between 5G and 6G, spectrum sharing and coexistence mechanisms to enable 6G in 7-15 GHz band, spectrum sharing and re-use for sustainability; overcoming limitations of variable numerology and, where deemed relevant, spectrum sharing with satellite, radar, or other terrestrial networks.
• Automation and disaggregation in the RAN segment: leveraging on open RAN architectures this area includes AI/ML powered automation and optimisation, micro-orchestration of RAN functions, programmable networks and API native, and exposure of network capabilities.
• Agile use of function accelerators at the 6G RAN/compute continuum which includes the integration of multi-processor SoC/accelerators, flexible and modular hardware/software architectures for communication-compute-control co-design, heterogeneous resource management, while meeting the new requirements and expectations on confidential computing solutions.

Note: Applicants may address a subset of the above priorities/areas. To facilitate the evaluation applicants should clearly identify the areas they are comprehensively addressing.

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