Shaping Future 6G Networks. Группа авторов
as a starting point to build innovative 6G protocol layers for both human‐oriented and machine‐oriented communications.
Then, as stated before, 5G has turned the mobile communications network into a pure software‐based system, exploiting the innovations of software‐defined networking and network function virtualization. In addition to cloud computing, which inspired new centralized service architectures, edge computing evolved as the new architectural principle to enable network function distribution for low‐latency communications and efficiency in network data processing. Chapter 10 proposes to go one step beyond in considering the network more as a distributed computer board than as a provider of pipes and forwarding mechanisms. Starting from the work on programmable networks (from active networks to software‐defined networking), the chapter introduces emerging concepts and requirements for the computerization of networks. While it breaks some established principles (e.g. end‐to‐end principle of the Internet or client‐server design), this enables to create a seamless core‐edge continuum of multiple independent components. Such continuum will require a programmable dataplane, relying on a common data layer. Potential application cases are, for example, the optimization of datacenter design, the next generation of IoT with intelligence everywhere, or computing support for networked AR/VR. We therefore believe 6G should be the opportunity to rethink the network as a programmable platform.
1.3.6 New Perspectives for Network Architectures (Chapters 11 and 12)
Trust has become a major aspect for the adoption of new mobile networking technologies, as they become critical infrastructures. This appears even more important when we consider the increasing interworking of different network domains. Since 2G, interconnection is standardized between mobile network operators for the roaming features. 5G introduces a new step with various private 5G networks that might be partly interconnected with public 5G networks. We believe this will increasingly be the case in future 6G networks, with various players providing connectivity and resources to deliver 6G services. Chapter 11 provides an overview of issues, requirements, and solutions to achieve a trustworthy inter‐domain collaboration in software‐defined environments. Authors focus on automating the delivery of multi‐domain services. They also discuss a set of challenges to address for the networking community to achieve collaborative 6G networks: security of operations, consistency of data and decisions, performance, and scalability.
One of 5G’s key achievements is the flexible network architecture defined by disaggregated network functions. This disaggregation has some tradition in the core network but will extend with the adoption of OpenRAN disaggregation principles also within the access network. Chapter 12 introduces more precisely the challenges to build such renewed 6G access networks. Starting from Cloud‐RAN and mobile edge computing, authors introduce the rise of intelligence and openness of the RAN components, leading to RAN disaggregation on all its dimensions (radio, compute, management plane, control plane). In line with the OpenRAN architecture, RAN intelligent controllers should be used as the key building block to enable both near real‐time and non‐real‐time 6G services. However, challenges remain to be tackled to shift from traditional tightly coupled RAN to disaggregated RAN, as for example: customized data collection and control, radio resource management, and air interface protocol processing decoupling, but also the need of open API to build an applicative ecosystem on the top of these RAN intelligent controllers.
1.3.7 New Technologies for Network Management and Operation (Chapters 13–15)
As discussed previously, the disaggregation principle with loosely coupled network functions (including in the RAN) will be at the core of the forthcoming 6G networks. This allows the dynamic orchestration of network functions and thus adaptation of the network to specific service requirements and network conditions in an end‐to‐end manner. In this context, monitoring and management of data will become the new fuel in networking. Chapter 13 addresses major development trends toward the definition of a data‐layer‐oriented network. It presumes the extraction of a large amount of data, its exchange across different elements, the generation of insight, and its immediate application as customized configurations across the system. A new type of network optimization is obtained based on user behavior instead of the one of the systems complimented by a large level of native automation.
Chapter 14 discusses opportunities given by the adoption of ML at the edge of wireless networks. The authors describe the latest in ML (e.g. Kernel‐based learning, deep learning, and reinforcement learning) and suggest application domains within the radio network exploiting the available domain knowledge, such as robust traffic prediction for energy optimization or optimized localization of end systems and beamforming optimization. They proclaim that ML will be the heart of future 6G architectures. Chapter 15 expands on the previous chapter by looking specifically at the adoption and standardization of AI/ML for secure, automated end‐to‐end slice orchestration and management, both at the edge and at the core of 6G mobile networks. The authors describe the rising use of AI/ML across the control protocol stack, investigating in particular the use of federated learning for optimal communication. They also introduce the challenges for global management of 6G systems that should perform smart resource management, automatic network adjustment, provisioning, and orchestration and rely on real‐time data insights to optimize network performance. Standardization should play a key role to achieve this goal, as already started with OpenRAN.
1.3.8 Post‐Shannon Perspectives (Chapter 16)
6G network will also be the opportunity to introduce innovative communication mechanisms. Chapter 16 lays out a disruptive view of 6G, addressing major innovations becoming possible by the new post‐Shannon theory. To truly achieve the potential gains of post‐Shannon communication, we have to break with the concept of a physical layer as a mere transport channel, as the needed algorithms cannot only rely on the softwarized higher layers. A new structure of the physical layer is required to integrate new communication tasks, such as message identification, secure message transmission, and CR (common randomness, i.e. correlated results of a random experiment) generation and extraction with higher layer policies that assign different logical channels for the different services. Chapter 16 provides comprehensive insights on these challenges and evolutions.
We hope you gain interesting insights into the major complementary research aspects of 6G summarized in the Figure 1.1.
Figure 1.1 Major trends toward 6G.
We are only at the beginning of a long journey toward 6G, which will hit the market by 2030 and provide the major communications infrastructure until 2040. The fun part is that although it will be a global race to generate new IP, ongoing globalization of our economic markets will necessitate close cooperation among researchers on different continents. We strongly believe that in the end, 6G will be the center of all future communications, connecting all people and things on this planet with infrastructures enabling