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Register a new user6G Massive Radio Access Networks: Key Issues, Technologies, and Future Challenges
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Driven by the emerging use cases in massive access future networks, there is a need for technological advancements and evolutions for wireless communications beyond the fifth-generation (5G) networks. In particular, we envisage the upcoming sixth-generation (6G) networks to consist of numerous devices demanding extremely high-performance interconnections even under strenuous scenarios such as diverse mobility, extreme density, and dynamic environment. To cater for such a demand, investigation on flexible and sustainable radio access network (RAN) techniques capable of supporting highly diverse requirements and massive connectivity is of utmost importance. To this end, this paper first outlines the key driving applications for 6G, including smart city and factory, which trigger the transformation of existing RAN techniques. We then examine and provide in-depth discussions on several critical performance requirements (i.e., the level of flexibility, the support for massive interconnectivity, and energy efficiency), issues, enabling technologies, and challenges in designing 6G massive RANs. We conclude the article by providing several artificial-intelligence-based approaches to overcome future challenges.
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Current network access infrastructures are characterized by heterogeneity, low latency, high throughput, and high computational capability, enabling massive concurrent connections and various services. Unfortunately, this design does not pay significant attention to mobile services in underserved areas. In this context, the use of aerial radio access networks (ARANs) is a promising strategy to complement existing terrestrial communication systems. Involving airborne components such as unmanned aerial vehicles, drones, and satellites, ARANs can quickly establish a flexible access infrastructure on demand. ARANs are expected to support the development of seamless mobile communication systems toward a comprehensive sixth-generation (6G) global access infrastructure. This paper provides an overview of recent studies regarding ARANs in the literature. First, we investigate related work to identify areas for further exploration in terms of recent knowledge advancements and analyses. Second, we define the scope and methodology of this study. Then, we describe ARAN architecture and its fundamental features for the development of 6G networks. In particular, we analyze the system model from several perspectives, including transmission propagation, energy consumption, communication latency, and network mobility. Furthermore, we introduce technologies that enable the success of ARAN implementations in terms of energy replenishment, operational management, and data delivery. Subsequently, we discuss application scenarios envisioned for these technologies. Finally, we highlight ongoing research efforts and trends toward 6G ARANs.
Network softwarization has revolutionized the architecture of cellular wireless networks. State-of-the-art container based virtual radio access networks (vRAN) provide enormous flexibility and reduced life cycle management costs, but they also come with prohibitive energy consumption. We argue that for future AI-native wireless networks to be flexible and energy efficient, there is a need for a new abstraction in network softwarization that caters for neural network type of workloads and allows a large degree of service composability. In this paper we present the NeuroRAN architecture, which leverages stateful function as a user facing execution model, and is complemented with virtualized resources and decentralized resource management. We show that neural network based implementations of common transceiver functional blocks fit the proposed architecture, and we discuss key research challenges related to compilation and code generation, resource management, reliability and security.
A plethora of demanding services and use cases mandate a revolutionary shift in the management of future wireless network resources. Indeed, when tight quality of service demands of applications are combined with increased complexity of the network, legacy network management routines will become unfeasible in 6G. Artificial Intelligence (AI) is emerging as a fundamental enabler to orchestrate the network resources from bottom to top. AI-enabled radio access and AI-enabled core will open up new opportunities for automated configuration of 6G. On the other hand, there are many challenges in AI-enabled networks that need to be addressed. Long convergence time, memory complexity, and complex behaviour of machine learning algorithms under uncertainty as well as highly dynamic channel, traffic and mobility conditions of the network contribute to the challenges. In this paper, we survey the state-of-art research in utilizing machine learning techniques in improving the performance of wireless networks. In addition, we identify challenges and open issues to provide a roadmap for the researchers.
With the open of the scale-up commercial deployment of 5G network, more and more researchers and related organizations began to consider the next generation of mobile communication system. This article will explore the 6G concept for 2030s. Firstly, this article summarizes the future 6G vision with four keywords: Intelligent Connectivity, Deep Connectivity, Holographic Connectivity and Ubiquitous Connectivity, and these four keywords together constitute the 6G overall vision of Wherever you think, everything follows your heart . Then, the technical requirements and challenges to realize the 6G vision are analyzed, including peak throughput, higher energy efficiency, connection every where and anytime, new theories and technologies, self-aggregating communications fabric, and some non-technical challenges. Then the potential key technologies of 6G are classified and presented: communication technologies on new spectrum, including terahertz communication and visible light communication; fundamental technologies, including sparse theory (compressed sensing), new channel coding technology, large-scale antenna and flexible spectrum usage; special technical features, including Space-Air-Ground-Sea integrated communication and wireless tactile network. By exploring the 6G vision, requirements and challenges, as well as potential key technologies, this article attempts to outline the overall framework of 6G, and to provide directional guidance for the subsequent 6G research. Keywords 6G, vision, terahertz, VLC, compressed sensing, free duplex, wireless tactile network
6G technology targets to revolutionize the mobility industry by revamping the role of wireless connections. In this article, we draw out our vision on an intelligent, cooperative, and sustainable mobility environment of the future, discussing how 6G will positively impact mobility services and applications. The scenario in focus is a densely populated area by smart connected entities that are mutually connected over a 6G virtual bus, which enables access to an extensive and always up-to-date set of context-sensitive information. The augmented dataset is functional to let vehicles engage in adaptive and cooperative learning mechanisms, enabling fully automated functionalities with higher communication integrity and reduced risk of accidents while being a sentient and collaborative processing node of the same ecosystem. Smart sensing and communication technologies are discussed herein, and their convergence is devised by the pervasiveness of artificial intelligence in centralized or distributed and federated network architectures.
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