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

Elhachmi, 2022 - Google Patents

Distributed reinforcement learning for dynamic spectrum allocation in cognitive radio‐based internet of things

Elhachmi, 2022

View PDF @Full View
Document ID
11772611146346717018
Author
Elhachmi J
Publication year
Publication venue
IET Networks

External Links

Snippet

Cognitive Radio (CR) with other advancements such as the Internet of things and machine learning has recently emerged as the main involved technique to use spectrum in an efficient manner. It can access the spectrum in a fully dynamic way and exploit the unused …
Continue reading at ietresearch.onlinelibrary.wiley.com (PDF) (other versions)

Classifications

    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W84/00Network topologies
    • H04W84/18Self-organizing networks, e.g. ad-hoc networks or sensor networks
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W72/00Local resource management, e.g. wireless traffic scheduling or selection or allocation of wireless resources
    • H04W72/04Wireless resource allocation
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W84/00Network topologies
    • H04W84/02Hierarchical pre-organized networks, e.g. paging networks, cellular networks, WLAN [Wireless Local Area Network] or WLL [Wireless Local Loop]
    • H04W84/04Large scale networks; Deep hierarchical networks
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W16/00Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/22Traffic simulation tools or models
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W16/00Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/14Spectrum sharing arrangements between different networks
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W40/00Communication routing or communication path finding
    • H04W40/02Communication route or path selection, e.g. power-based or shortest path routing
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W16/00Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/24Cell structures
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W28/00Network traffic or resource management
    • H04W28/02Traffic management, e.g. flow control or congestion control
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W40/00Communication routing or communication path finding
    • H04W40/24Connectivity information management, e.g. connectivity discovery or connectivity update
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W28/00Network traffic or resource management
    • H04W28/16Central resource management; Negotiation of resources or communication parameters, e.g. negotiating bandwidth or QoS [Quality of Service]
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W48/00Access restriction; Network selection; Access point selection
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W4/00Mobile application services or facilities specially adapted for wireless communication networks
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W24/00Supervisory, monitoring or testing arrangements
    • 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
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00Arrangements for maintenance or administration or management of packet switching networks
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00Network-specific arrangements or communication protocols supporting networked applications

Similar Documents

Publication Publication Date Title
Seid et al. Collaborative computation offloading and resource allocation in multi-UAV-assisted IoT networks: A deep reinforcement learning approach
Li et al. Applications of multi-agent reinforcement learning in future internet: A comprehensive survey
Natarajan et al. An IoT and machine learning‐based routing protocol for reconfigurable engineering application
Bogale et al. Machine intelligence techniques for next-generation context-aware wireless networks
Hu et al. Vehicular multi-access edge computing with licensed sub-6 GHz, IEEE 802.11 p and mmWave
Nomikos et al. A survey on reinforcement learning-aided caching in heterogeneous mobile edge networks
Wang et al. Resource management for edge intelligence (EI)-assisted IoV using quantum-inspired reinforcement learning
Jang et al. Reinforcement learning-based dynamic band and channel selection in cognitive radio ad-hoc networks
Alwarafy et al. The frontiers of deep reinforcement learning for resource management in future wireless HetNets: Techniques, challenges, and research directions
Elhachmi Distributed reinforcement learning for dynamic spectrum allocation in cognitive radio‐based internet of things
Paul et al. Machine learning for spectrum information and routing in multihop green cognitive radio networks
Khozeimeh et al. Brain-inspired dynamic spectrum management for cognitive radio ad hoc networks
Naveen Raj et al. A survey and performance evaluation of reinforcement learning based spectrum aware routing in cognitive radio ad hoc networks
Islam et al. Survey on the state-of-the-art in device-to-device communication: A resource allocation perspective
Ashtari et al. Knowledge-defined networking: Applications, challenges and future work
Asuquo et al. Optimized channel allocation in emerging mobile cellular networks
Montero et al. Proactive radio-and QoS-aware UAV as BS deployment to improve cellular operations
Rajendran et al. Distributed coalition formation game for enhancing cooperative spectrum sensing in cognitive radio ad hoc networks
Mughal et al. An intelligent channel assignment algorithm for cognitive radio networks using a tree-centric approach in IoT
Rohoden et al. Evolutionary game theoretical model for stable femtocells’ clusters formation in hetnets
Arnous et al. ILFCS: an intelligent learning fuzzy-based channel selection framework for cognitive radio networks
Kim Heterogeneous Network Spectrum Allocation Scheme for Network‐Assisted D2D Communications
Sonti et al. Enhanced fuzzy C‐means clustering based cooperative spectrum sensing combined with multi‐objective resource allocation approach for delay‐aware CRNs
Bennaceur et al. Hierarchical game-based secure data collection with trust and reputation management in the cognitive radio network
Cheena et al. Deep Q-probabilistic algorithm based rock hyraxes swarm optimization for channel allocation in CRSN smart grids