At the dawn of 6G wireless networks, there are several challenges that need to be addressed. There is a need for ultra-high data rates to serve a huge number of wireless devices with different services (such as holographic communications, and Internet of Things). Low-latency and ultra-reliable communications are also important. In addition, there is growing demand for green communications to limit the ecological impact of cellular networks. Therefore, highest-level of energy-efficiency are also of crucial importance at a time where communications are about to reach 3 and up to 14% of global CO2 emissions by 2040.
In this dynamic and complex network ecosystem, revolutionary technologies are primordial to effectively deal with the diverse requirements imposed by the technical, environmental and societal concerns. To this end, researchers in industry and academia have massively investigated three enablers for effective and greener communications: (i) distributed antenna systems, also known as cell-free networks, (ii) reconfigurable intelligent surfaces (RIS) and (iii) Artificial Intelligence (AI)-aided signal processing modules.
Cell-free massive MIMO (CF-mMIMO) technology, which ensures macro-diversity gain and offers uniformly good spectral efficiency (SE) over the coverage area, avoids the cell boundaries and then its related inter-cell interference, a limiting factor of today's cellular networks. This is a considerable paradigm shift that can overcome the limitations of existing networks, dealing with the challenges of the future generations of wireless communications (B5G and 6G). RIS-aided CF-mMIMO can be a very promising solution, even for low frequency bands, to improve the link quality for improved spectral efficiency. On the other hand, AI tools are capable of building efficient signal processing based solutions, overcoming problems related to the high complexity and latency. Nevertheless, CF-mMIMO has been evaluated through theoretical assumptions and models, in the existing literature. Therefore, it is relevant and timely to evaluate the performance of this  technology though realistic distributed MIMO propagation channel, RIS modeling and careful considerations of the different hardware impairments.
To this end, the NF-PERSEUS project (PEPR-5G PC3) aims at increasing the maturity of these techniques towards achieving power and spectral efficient massive access in scalable B5G sub-7GHz networks. Specifically, NF-PERSEUS targets to propose robust PHY and MAC layers based on signal propagation measurements and the incorporation of hardware impairment models. Efficient resource allocation should be targeted through cutting-edge user clustering, antenna selection/collaboration and Non-Orthogonal Multiple Access (NOMA) schemes. Managing interference is key for their successful application. This requires the support of physical layer techniques such as multiple-access waveform. The latter can achieve improved robustness to channel impairments and fine synchronization while reducing multi-user interference through different numerologies, required to accommodate heterogeneous QoS requirements. MIMO precoding, reliable channel estimation/equalization, improved link quality through the exploitation of RIS and advanced error correcting codes represent additional key enabling techniques. These techniques should be based on realistic propagation and hardware impairment (HWI) models, leading to practical solutions. Finally, having such stringent requirements dictates the minimization of the impact of future hardware implementations on the predicted gains of the proposed solutions, as well. Therefore, the study of efficient power amplifier architectures and of the feasibility and performance of advanced antenna structures such as reconfigurable MIMO array, miniature antennas and RIS panels, will also be tackled.
Powered by the complementary skills of the consortium alliance, NF-PERSEUS will go beyond the existing literature emphasizing demonstration and evaluation studies. This will open opportunities for patents, realistic demonstrations and publications in the pre-standardization period of 6G.