Complex Systems: A Communication Networks Perspective towards 6G
Over the last few years, the analysis and modeling of networks as well as the analysis and modeling of networked dynamical systems, has attracted considerable interdisciplinary interest, especially using the complex systems theory. These efforts are driven by the fact that systems, as diverse as genetic networks or the Internet can be effectively described as complex networks. Contrary, despite the unprecedented evolution of technology, basic issues and fundamental principles related to the
... ctural and evolutionary properties of communication networks still remain largely unaddressed. The situation is even more complicated when we attempt to model the mobile communication networks and especially the 5th generation (5G) and eventually the forthcoming 6th generation (6G). In this work, we attempt to review basic models of complex networks from a communication networks perspective, focusing on their structural and evolutionary properties. Based on this review we aim to reveal the models of complex networks, that may apply when modeling the 5G and 6G mobile communication networks. Furthermore, we expect to encourage the collaboration between complex systems and networking theorists toward meeting the challenging demands of 5G networks and beyond. INDEX TERMS Complex systems, complex networks, networked complex system, 5G, 6G, wireless communications, wireless networks, mobile communication networks, modeling. VOLUME 8, 2020 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ 89007 C. Sergiou et al.: Complex Systems: Communication Networks Perspective Towards 6G theory studies how patterns emerge through the interaction of many interacting elements. In this space, emergent patterns can be perceived but can hardly be, if at all, predicted. Patterns may indeed repeat for a time, but we cannot be sure that they will continue to repeat, because the underlying sources of the patterns are not open to inspection (and observation of the system may itself disrupt the patterns) . Newman  , state that there are three interrelated approaches to the study of networked complex systems. These are: (a) find statistical properties, such as path length and degree distribution that characterize the structure and dynamic behavior of networked systems, (b) build models of networks that explain and help understand how they are created and how they evolve, and (c) predict the behavior of networked systems based on the measured statistical properties of the structure and the local properties of given vertices (study pattern formation and evolution). Nowadays, systems become increasingly larger acquiring even more components, while the information flow in the system increases at a fast pace. Mobile communication networks and especially the 5G and the forthcoming 6G, are typical examples of systems that expand rapidly. Mastering their complexity (the high level of interdependence between their, often, very heterogeneous components), becomes a major hurdle, threatening to disrupt the information revolution. Designing, controlling, modeling and monitoring the behavior of such systems are the fundamental challenges that should be addressed. We need new paradigms as we are rapidly moving from systems based on closed hierarchical or semi-hierarchical structures to open and distributed, networked systems. From a communication networks perspective, the key challenge is to learn how to design such networks that can self-organize, self-adapt and optimize their interactions and functions, in a continuous and robust manner to satisfy user demand. Fundamentally, the complex systems field can provide models, theories, mechanisms and approaches that allow for a principled design method to be developed, to address this key challenge. Mobile communications networks and especially the forthcoming 5G networks, as well as the future 6G networks, are getting more complicated and heterogeneous. The typical operation of these networks with denser deployments, more base stations, countless users, as well as the new technologies that are expected to be introduced in 6G networks like the Artificial Intelligence (AI), Machine Learning (ML), Terahertz (THz) band communications, etc renders any known information theory incapable to directly model the behavior and their dynamics. This is further exacerbated, by the trend toward the softwarisation of networking functionalities and the dynamic orchestration of networked services  . Complex systems theory could become a useful and effective tool capable to model at some degree the behaviour of these networks. In this paper we present complex systems from a communication networks perspective, revealing the issues and challenges as well as the way forward, towards 6G mobile communication networks. This work complements and extends the Technical Report TR-07-01 , with a focus on 5G/6G communication networks. Whilst the main focus of the study is 6G, most of the discussion is directly relevant to the evolving 5G. The rest of the paper is organized as follow: In Section II, we briefly present some of the new challenges that are expected to be introduced in 5G/6G Wireless Communication Networks. In Section III we present the basic concepts of complex networks that are foreseen to appear in 6G. In Section IV we present the Complex Adaptive Systems (CAS) Properties while in Section V we present specific network modeling paradigms. In Section VI we introduce the mobile communication networks as complex systems and finally in Section VII a proposed way of modeling the 6G networks. Finally, in Section VIII we present our conclusions.