Self-Evolving Integrated Vertical Heterogeneous Networks

The evolution of future networks into fully autonomous entities appears inevitable. The need for greater operational agility in supporting a wide range of services and use cases together with increasing network complexity creates, in all likelihood, unforeseen new challenges. 6G and beyond networks will have a disruptive architecture imposing some crucial requirements: 1) Support universal access to intelligence sustained by a distributed computing, sensing, and control infrastructure; 2) manage with a unified framework of a heterogeneous communication, computing, caching, and control infrastructure; 3) support highly dynamic and possibly intermittent networks of vertical networks. This study first advocates the merits of integrated vertical heterogeneous network (VHetNet) architecture in support of 6G infrastructure. We then review the current literature on network management of vertical networks and discuss a unified network management framework to analyze new architecture-dependent challenges and their coordination with existing network management services and requirements. Third, we investigate recent advancements in artificial intelligence (AI)/machine learning (ML) methods in current VHetNets and discuss the core challenges of integrating AI/ML in VHetNets. Finally, we discuss potential future research directions for advancing the autonomous and evolving capabilities of VHetNets.