[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Zhou et al., 2024 - Google Patents

An overview of machine learning-enabled optimization for reconfigurable intelligent surfaces-aided 6g networks: From reinforcement learning to large language …

Zhou et al., 2024

View PDF
Document ID
3604628524213556433
Author
Zhou H
Hu C
Liu X
Publication year
Publication venue
arXiv preprint arXiv:2405.17439

External Links

Snippet

Reconfigurable intelligent surface (RIS) becomes a promising technique for 6G networks by reshaping signal propagation in smart radio environments. However, it also leads to significant complexity for network management due to the large number of elements and …
Continue reading at arxiv.org (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/04Inference methods or devices
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063Operations research or analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models

Similar Documents

Publication Publication Date Title
Shi et al. Machine learning for large-scale optimization in 6g wireless networks
Wei et al. Joint optimization of caching, computing, and radio resources for fog-enabled IoT using natural actor–critic deep reinforcement learning
Qi et al. Knowledge-driven service offloading decision for vehicular edge computing: A deep reinforcement learning approach
He et al. An overview on the application of graph neural networks in wireless networks
Gacanin et al. Wireless 2.0: Toward an intelligent radio environment empowered by reconfigurable meta-surfaces and artificial intelligence
Dahrouj et al. An overview of machine learning-based techniques for solving optimization problems in communications and signal processing
Heidari et al. A hybrid approach for latency and battery lifetime optimization in IoT devices through offloading and CNN learning
Liu et al. Distributed intelligence in wireless networks
Hlophe et al. AI meets CRNs: A prospective review on the application of deep architectures in spectrum management
Chen et al. Profit-aware cooperative offloading in uav-enabled mec systems using lightweight deep reinforcement learning
Qi et al. Vehicular edge computing via deep reinforcement learning
Munir et al. Neuro-symbolic explainable artificial intelligence twin for zero-touch IoE in wireless network
Le et al. Applications of distributed machine learning for the internet-of-things: A comprehensive survey
Zhou et al. An overview of machine learning-enabled optimization for reconfigurable intelligent surfaces-aided 6g networks: From reinforcement learning to large language models
Cheng et al. Deep learning for wireless networking: The next frontier
Ji et al. Graph neural networks and deep reinforcement learning based resource allocation for v2x communications
Nguyen et al. Applications of deep learning and deep reinforcement learning in 6G networks
Zhang et al. Decision Transformers for Wireless Communications: A New Paradigm of Resource Management
Zhang et al. Joint user association and power allocation in heterogeneous ultra dense network via semi-supervised representation learning
Hua et al. Learning-based reconfigurable-intelligent-surface-aided rate-splitting multiple access networks
Fan et al. MEC network slicing: Stackelberg-game-based slice pricing and resource allocation with QoS guarantee
Abbasi et al. Optimizing UAV computation offloading via MEC with deep deterministic policy gradient
Zhang et al. Effective 3C resource utilization and fair allocation strategy for multi-task federated learning
Le et al. Applications of distributed machine learning for the Internet-of-Things: A comprehensive survey
She et al. Ultra-Reliable and Low-Latency Communications in 6G: Challenges, Solutions, and Future Directions