Intelligent and Programmable Interoperability for the 6G network-of-networks

The evolution of wireless network architectures from 3G to 5G has witnessed significant advancements in both Radio Access Network (RAN) and Core Network designs. In 3G, RAN primarily relied on circuit-switched networks, while 4G introduced the Long-Term Evolution (LTE) standard, shifting towards an all-IP architecture, improving data rates, and enhancing network efficiency.  With 5G, the architectural transformation became more pronounced. RAN adopted a highly flexible and scalable approach with the introduction of Massive MIMO, beamforming, and mmWave frequencies, enabling higher data rates and ultra-low latency, along reliability. The Core Network evolved to accommodate network slicing, edge computing, and virtualization, allowing for tailored services and efficient resource allocation. Both RAN and Core have been empowered by the flexibility brought by several network-softwarization methods and techniques, such as NFV, SDR, SDN, including orchestration at both network and service level. 

As we look forward to 6G, the network architecture for the 6^th generation is poised to become the "network of networks." It will seamlessly integrate various technologies, including softwarized AI-driven networks, terahertz frequencies, and satellite networks. This architecture aims to provide ubiquitous connectivity, extreme data rates, sub-millisecond latency, and support for billions of devices. The key research questions to be explored under this PhD thesis is: will 6G architecture rely on a decentralized, self-organizing, and highly resilient network infrastructure? If so, how should the architecture be? will 6G disrupt the legacy RAN and Core? To answer those questions the candidate:

• Will understand the 6G connectivity requirements in terms of performance, energy consumption and sustainability, coming from use cases and verticals such as holographic communication, immersive augmented reality, and instant global access, revolutionizing industries like healthcare, transport and logistics, and entertainment.
• Will understand the different features (frequencies, modulation schemes, topologies, IP routing) of the different networks that will converge into the network of networks such as 3GPP (5G, 6G) and non-3GPP (Wi-Fi, Non-terrestrials) based networks. 
• Will identify and report the different requirements that both hardware and software should deliver from radio front-ends to computing capabilities.
• Ultimately, the candidate will design schemes and algorithms to enable AI-based-programmable interoperability among the different networks, thus realizing the so called “network-of-networks”