Control-data separation architecture for cellular radio access networks: a survey and outlook

Conventional cellular systems are designed to ensure ubiquitous coverage with an always present wireless channel irrespective of the spatial and temporal demand of service. This approach raises several problems due to the tight coupling between network and data access points, as well as the paradigm shift towards data-oriented services, heterogeneous deployments and network densification. A logical separation between control and data planes is seen as a promising solution that could overcome these issues, by providing data services under the umbrella of a coverage layer. This article presents a holistic survey of existing literature on the control-data separation architecture (CDSA) for cellular radio access networks. As a starting point, we discuss the fundamentals, concepts, and general structure of the CDSA. Then, we point out limitations of the conventional architecture in futuristic deployment scenarios. In addition, we present and critically discuss the work that has been done to investigate potential benefits of the CDSA, as well as its technical challenges and enabling technologies. Finally, an overview of standardisation proposals related to this research vision is provided

Cognition-inspired 5G cellular networks: a review and the road ahead

Despite the evolution of cellular networks, spectrum scarcity and the lack of intelligent and autonomous capabilities remain a cause for concern. These problems have resulted in low network capacity, high signaling overhead, inefficient data forwarding, and low scalability, which are expected to persist as the stumbling blocks to deploy, support and scale next-generation applications, including smart city and virtual reality. Fifth-generation (5G) cellular networking, along with its salient operational characteristics - including the cognitive and cooperative capabilities, network virtualization, and traffic offload - can address these limitations to cater to future scenarios characterized by highly heterogeneous, ultra-dense, and highly variable environments. Cognitive radio (CR) and cognition cycle (CC) are key enabling technologies for 5G. CR enables nodes to explore and use underutilized licensed channels; while CC has been embedded in CR nodes to learn new knowledge and adapt to network dynamics. CR and CC have brought advantages to a cognition-inspired 5G cellular network, including addressing the spectrum scarcity problem, promoting interoperation among heterogeneous entities, and providing intelligence and autonomous capabilities to support 5G core operations, such as smart beamforming. In this paper, we present the attributes of 5G and existing state of the art focusing on how CR and CC have been adopted in 5G to provide spectral efficiency, energy efficiency, improved quality of service and experience, and cost efficiency. This main contribution of this paper is to complement recent work by focusing on the networking aspect of CR and CC applied to 5G due to the urgent need to investigate, as well as to further enhance, CR and CC as core mechanisms to support 5G. This paper is aspired to establish a foundation and to spark new research interest in this topic. Open research opportunities and platform implementation are also presented to stimulate new research initiatives in this exciting area

Five Facets of 6G: Research Challenges and Opportunities

Whilst the fifth-generation (5G) systems are being rolled out across the globe, researchers have turned their attention to the exploration of radical next-generation solutions. At this early evolutionary stage we survey five main research facets of this field, namely {\em Facet~1: next-generation architectures, spectrum and services, Facet~2: next-generation networking, Facet~3: Internet of Things (IoT), Facet~4: wireless positioning and sensing, as well as Facet~5: applications of deep learning in 6G networks.} In this paper, we have provided a critical appraisal of the literature of promising techniques ranging from the associated architectures, networking, applications as well as designs. We have portrayed a plethora of heterogeneous architectures relying on cooperative hybrid networks supported by diverse access and transmission mechanisms. The vulnerabilities of these techniques are also addressed and carefully considered for highlighting the most of promising future research directions. Additionally, we have listed a rich suite of learning-driven optimization techniques. We conclude by observing the evolutionary paradigm-shift that has taken place from pure single-component bandwidth-efficiency, power-efficiency or delay-optimization towards multi-component designs, as exemplified by the twin-component ultra-reliable low-latency mode of the 5G system. We advocate a further evolutionary step towards multi-component Pareto optimization, which requires the exploration of the entire Pareto front of all optiomal solutions, where none of the components of the objective function may be improved without degrading at least one of the other components