SpectrumChain: a disruptive dynamic spectrum-sharing framework for 6G

Wu, Qihui; Wang, Wei; Li, Zuguang; Zhang, Bo; Huang, Yang; Wang, Xianbin

doi:10.1007/s11432-022-3692-5

Cited by 30 publications

(4 citation statements)

References 45 publications

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“…5 , we also qualitatively present the results of the ablation comparison. It shows that when the framework lacks NTN, the surface of the 3D model is smooth without the texture [ 60 ], detail, and shape. When the MEGN is missing, the sketch of the generative model are unclear.…”

Section: Resultsmentioning

confidence: 99%

Cross-Modal Graph Semantic Communication Assisted by Generative AI in the Metaverse for 6G

Chen,

Liu,

Wang

et al. 2024

Research

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Recently, the development of the Metaverse has become a frontier spotlight, which is an important demonstration of the integration innovation of advanced technologies in the Internet. Moreover, artificial intelligence (AI) and 6G communications will be widely used in our daily lives. However, the effective interactions with the representations of multimodal data among users via 6G communications is the main challenge in the Metaverse. In this work, we introduce an intelligent cross-modal graph semantic communication approach based on generative AI and 3-dimensional (3D) point clouds to improve the diversity of multimodal representations in the Metaverse. Using a graph neural network, multimodal data can be recorded by key semantic features related to the real scenarios. Then, we compress the semantic features using a graph transformer encoder at the transmitter, which can extract the semantic representations through the cross-modal attention mechanisms. Next, we leverage a graph semantic validation mechanism to guarantee the exactness of the overall data at the receiver. Furthermore, we adopt generative AI to regenerate multimodal data in virtual scenarios. Simultaneously, a novel 3D generative reconstruction network is constructed from the 3D point clouds, which can transfer the data from images to 3D models, and we infer the multimodal data into the 3D models to increase realism in virtual scenarios. Finally, the experiment results demonstrate that cross-modal graph semantic communication, assisted by generative AI, has substantial potential for enhancing user interactions in the 6G communications and Metaverse.

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Section: Resultsmentioning

confidence: 99%

Cross-Modal Graph Semantic Communication Assisted by Generative AI in the Metaverse for 6G

Chen,

Liu,

Wang

et al. 2024

Research

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show abstract

“…The 6G networks will have more capacity as well as better coverage. Additionally, several cutting-edge methods are being used by 6G technology to increase coverage, including IRS cells [69], adaptive modulation/coding [70], adaptive/geometrical beamforming [71], AI quantum computing [72], blockchain technology [73], and more. To further increase capacity, 6G technology is also utilizing leadingedge technologies such as massive MIMO [74], mmWave technologies [75], T-Hz communication [76], VLC [77], and non-orthogonal multiple access (NOMA) [78].…”

Section: Network Capacity and Coverage In Ai-ran 6gmentioning

confidence: 99%

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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“…For example, prevalent research in active compliance and force sensing depends on force sensors located at either the proximal or distal extremities of robots, which complicates the system. Wu et al [ 294 ] introduced a novel approach, utilizing tip‐pose feedback for active compliance and force estimation, thereby obviating the need for supplementary sensors apart from an endoscopic camera. In some scenarios, a single‐continuum robot might prove insufficient for task completion, necessitating the orchestration of multiple such robots.…”

Section: State‐of‐the‐art Continuum Robotics Technology For Endoscopi...mentioning

confidence: 99%

Toward Bionic Arthroscopy: A Comprehensive Perspective of Continuum Robotics Principles and Prototypes for the Inception of Arthroscopic Surgery Robots

Huang,

Shi,

Gao

et al. 2023

Advanced Intelligent Systems

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In this study, an innovative exploration of leveraging bionics and continuum robotics principles to develop a novel solution for arthroscopic surgery is embarked on. Inspired by the flexibility and adaptability of organisms like snakes and octopuses, the continuum robot concept aims to address the inherent challenges in traditional arthroscopy, including lower precision, manual tremors, and long surgeon learning curves. The implementation of these principles in the human body, however, faces significant obstacles, particularly achieving high‐performance motion control amid strong nonlinearity and coupling between modules. This research focuses on intelligent integration and enhanced safety in human‐machine interaction, aiming for improved control precision and flexibility in arthroscopic procedures. A thorough literature review of endoscopic continuum robots is conducted, highlighting current advancements in actuation, structure, sensing, and control technologies. The study concludes with an assessment of these technologies, their limitations, and future potential, in light of the unique demands of arthroscopic continuum robots. This comprehensive review bridges bionics and robotics, presenting the opportunities and challenges in applying continuum robotics to arthroscopic surgery. The goal is to encourage further research in this area, contributing to the development of prototype robots that enhance the precision and safety of arthroscopic surgery.

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SpectrumChain: a disruptive dynamic spectrum-sharing framework for 6G

Cited by 30 publications

References 45 publications

Cross-Modal Graph Semantic Communication Assisted by Generative AI in the Metaverse for 6G

Cross-Modal Graph Semantic Communication Assisted by Generative AI in the Metaverse for 6G

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

Toward Bionic Arthroscopy: A Comprehensive Perspective of Continuum Robotics Principles and Prototypes for the Inception of Arthroscopic Surgery Robots

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