6G CloudNet: Towards a Distributed, Autonomous, and Federated AI-Enabled Cloud and Edge Computing

Alimi, Isiaka A.; Patel, Romil K.; Zaouga, Aziza; Muga, Nelson J.; Pinto, Armando N.; Teixeira, A.; Monteiro, Paulo P.

doi:10.1007/978-3-030-72777-2_13

Cited by 4 publications

(7 citation statements)

References 47 publications

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“…Basically, it is envisaged to transform mobile networks and considerably improve the existing 4G/LTE network performance. Furthermore, it is expected to support many advanced radio technologies such as network slicing, to facilitate quick deployment of different services; Information-Centric Networking (ICN), for the reduction in network traffic; Software-Defined Networks (SDN), to ensure sufficient network flexibility; and Massive MIMO and millimeter-wave for enhancing the system capacity [218,219]. Moreover, it is envisaged to deliver enhanced transmission rates with a minimum rate of 1 Gbps so as to offer an outstanding mobile experience through an eMBB.…”

Section: Mobile Network Evolutionmentioning

confidence: 99%

“…Apart from the performance improvement regarding substantial high data rates and low latency, massive connection density based on massive machine-type communications (mMTC), as well as other improvements, are anticipated. In this context, use cases such as mMTC, eMBB, and URLLC have been defined by the International Telecommunication Union (ITU) for the 5G networks [218]. Furthermore, the 5G system is a converged network in which wired and wireless systems are to exploit the same infrastructure [220].…”

Section: Mobile Network Evolutionmentioning

confidence: 99%

“…Besides, like its predecessor networks, 5G might not be able to stand the test of time in offering future system requirements regarding full connectivity. Therefore, research attention should be focusing on beyond 5G wireless communications [218]. (vi) Network 2030 and Beyond: The low-frequency spectrum band is capable of longdistance propagation and consequently can support wide coverage.…”

Section: Mobile Network Evolutionmentioning

confidence: 99%

“…The Group aims to guide the global information and communications technology (ICT) community in the analysis of the network capability for the year 2030 and beyond. In this context, some extensive researches are ongoing regarding 6G [218,221]. Moreover, 6G is envisioned to be based on major innovative technologies such as super Internet-of-Things (IoT), mobile ultra-broadband, and AI.…”

Section: Mobile Network Evolutionmentioning

confidence: 99%

“…Furthermore, super IoT can be achieved with symbiotic radio and satellite-assisted communications. Besides, machine learning methods are expected to be promising solutions for AI networks [218,221,222]. As summarized in Table 7, 6G is envisaged to offer a considerable improvement on the 5G by employing AI to automate and optimize its operation.…”

Section: Mobile Network Evolutionmentioning

confidence: 99%

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Towards Enhanced Mobile Broadband Communications: A Tutorial on Enabling Technologies, Design Considerations, and Prospects of 5G and beyond Fixed Wireless Access Networks

et al. 2021

Self Cite

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There has been a growing interconnection across the world owing to various multimedia applications and services. Fixed wireless access (FWA) is an attractive wireless solution for delivering multimedia services to different homes. With the fifth-generation (5G) and beyond mobile networks, the FWA performance can be enhanced significantly. However, their implementation will present different challenges on the transport network due to the incessant increase in the number of required cell-sites and the subsequent increase in the per-site requirements. This paper presents a comprehensive tutorial on the enabling technologies, design considerations, requirements, and prospects of broadband schemes. Furthermore, the related technical challenges of FWA are reviewed, and we proffer potential solutions to address them. Besides, we review various transport network options that can be employed for FWA deployment. In this regard, we offer an in-depth discussion on their related requirements for different use cases. Moreover, we give an insight into the 3GPP RAN functional split implementations and implications on the 5G FWA transport network solutions. The concepts of virtualized RANs for attending flexibly to the dynamic nature of different use cases are also presented.

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Section: Mobile Network Evolutionmentioning

confidence: 99%

Section: Mobile Network Evolutionmentioning

confidence: 99%

Section: Mobile Network Evolutionmentioning

confidence: 99%

Section: Mobile Network Evolutionmentioning

confidence: 99%

Section: Mobile Network Evolutionmentioning

confidence: 99%

See 3 more Smart Citations

Towards Enhanced Mobile Broadband Communications: A Tutorial on Enabling Technologies, Design Considerations, and Prospects of 5G and beyond Fixed Wireless Access Networks

et al. 2021

Self Cite

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6G Based Green Mobile Edge Computing for Internet of Things (IoT)

Mukherjee

Panja²,

Obaidat³

et al. 2022

Green Mobile Cloud Computing

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AI-RAN in 6G Networks: State-of-the-Art and Challenges

Khan,

Schmid

2024

IEEE Open J. Commun. Soc.

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6G is a next-generation cellular communication technology that builds up on existing 5G networks which are currently rolled out worldwide. Through incorporation of artificial intelligence (AI) and machine learning (ML), the core 5G network is advanced into an intelligent 6G network. The 6G Artificial Intelligence Radio Access Network (AI-RAN) is anticipated to offer advanced features like reduced latency, improved bandwidth, data rates and coverage. Furthermore, AI-RAN is expected to support complex use cases such as extreme connectivity, multi-user communications and dynamic spectrum access. This paper provides a detailed survey and thorough assessment of AI-RAN's vision and state-of-the-art challenges. We first present a concise introduction to 6G AI-RAN followed by background information on the current 5G RAN and its challenges that must be overcome to implement 6G AI-RAN. The paper then examines trending research issues in AI-RAN, i.e., challenges related to spectrum allocation, network architecture, and resource management. We discuss the methods to overcome these challenges which include the adoption of advanced machine learning and edge computing technologies to boost the performance of 6G AI-RAN. We conclude by stating open research directions.

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6G CloudNet: Towards a Distributed, Autonomous, and Federated AI-Enabled Cloud and Edge Computing

Cited by 4 publications

References 47 publications

Towards Enhanced Mobile Broadband Communications: A Tutorial on Enabling Technologies, Design Considerations, and Prospects of 5G and beyond Fixed Wireless Access Networks

Towards Enhanced Mobile Broadband Communications: A Tutorial on Enabling Technologies, Design Considerations, and Prospects of 5G and beyond Fixed Wireless Access Networks

6G Based Green Mobile Edge Computing for Internet of Things (IoT)

AI-RAN in 6G Networks: State-of-the-Art and Challenges

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