Nothing Special   »   [go: up one dir, main page]

Sun et al., 2020 - Google Patents

Spatial and temporal contextual multi-armed bandit handovers in ultra-dense mmWave cellular networks

Sun et al., 2020

View PDF
Document ID
16978525245090031966
Author
Sun L
Hou J
Shu T
Publication year
Publication venue
IEEE Transactions on Mobile Computing

External Links

Snippet

Although millimeter wave (mmWave) is a promising technology in 5G communication, its severe path attenuation and susceptibility to line-of-sight (LOS) blockage result in much more unpredictable outages than traditional technologies. This special propagation property …
Continue reading at ieeexplore.ieee.org (PDF) (other versions)

Classifications

    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W36/00Hand-off or reselection arrangements
    • H04W36/24Reselection being triggered by specific parameters used to improve the performance of a single terminal
    • H04W36/30Reselection being triggered by specific parameters used to improve the performance of a single terminal by measured or perceived connection quality data
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W36/00Hand-off or reselection arrangements
    • H04W36/16Performing reselection for specific purposes
    • H04W36/18Performing reselection for specific purposes for allowing seamless reselection, e.g. soft reselection
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W36/00Hand-off or reselection arrangements
    • H04W36/24Reselection being triggered by specific parameters used to improve the performance of a single terminal
    • H04W36/32Reselection being triggered by specific parameters used to improve the performance of a single terminal by location or mobility data, e.g. speed data
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B7/00Radio transmission systems, i.e. using radiation field
    • H04B7/02Diversity systems; Multi-antenna systems, i.e. transmission or reception using multiple antennas
    • H04B7/022Site diversity; Macro-diversity
    • H04B7/024Co-operative use of antennas of several sites, e.g. in co-ordinated multipoint or co-operative multiple-input multiple-output [MIMO] systems
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B7/00Radio transmission systems, i.e. using radiation field
    • H04B7/02Diversity systems; Multi-antenna systems, i.e. transmission or reception using multiple antennas
    • H04B7/04Diversity systems; Multi-antenna systems, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/08Diversity systems; Multi-antenna systems, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • 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
    • H04W36/00Hand-off or reselection arrangements
    • H04W36/0005Control or signalling for completing the hand-off
    • 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
    • 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
    • H04W4/00Mobile application services or facilities specially adapted for wireless communication networks
    • H04W4/02Mobile application Services making use of the location of users or terminals, e.g. OMA SUPL, OMA MLP or 3GPP LCS
    • H04W4/025Mobile application Services making use of the location of users or terminals, e.g. OMA SUPL, OMA MLP or 3GPP LCS using location based information parameters
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W24/00Supervisory, monitoring or testing arrangements
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W48/00Access restriction; Network selection; Access point selection
    • H04W48/20Selecting an access point
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W64/00Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Similar Documents

Publication Publication Date Title
Sun et al. Spatial and temporal contextual multi-armed bandit handovers in ultra-dense mmWave cellular networks
Yan et al. Machine learning-based handovers for sub-6 GHz and mmWave integrated vehicular networks
US20220190883A1 (en) Beam prediction for wireless networks
Zang et al. Managing vertical handovers in millimeter wave heterogeneous networks
Khosravi et al. Learning-based handover in mobile millimeter-wave networks
Lee et al. Intelligent dual active protocol stack handover based on double DQN deep reinforcement learning for 5G mmWave networks
Palas et al. Multi-criteria handover mobility management in 5G cellular network
CN111328065B (en) Dynamic programming-based mobility cooperative management method for 5G cloud access network
Sun et al. Optimal handover policy for mmWave cellular networks: A multi-armed bandit approach
CN105208615A (en) Switching method based on adjustable prediction threshold hysteresis margin in super-dense network
Cao et al. Deep reinforcement learning for multi-user access control in UAV networks
JP2023085217A (en) User equipment trajectory based beam selection
Ahuja et al. Particle swarm optimization based network selection in heterogeneous wireless environment
Satapathy et al. An efficient multicriteria‐based vertical handover decision‐making algorithm for heterogeneous networks
HajiAkhondi-Meybodi et al. Mobility-aware femtocaching algorithm in D2D networks based on handover
Zarifneshat et al. Learning-based blockage prediction for robust links in dynamic millimeter wave networks
Lee et al. DQN based user association control in hierarchical mobile edge computing systems for mobile IoT services
Chen et al. 1 A deep reinforcement learning framework to combat dynamic blockage in mmWave V2X networks
Mollel et al. Handover management in dense networks with coverage prediction from sparse networks
Van Huynh et al. Optimal beam association for high mobility mmWave vehicular networks: Lightweight parallel reinforcement learning approach
Gures et al. A comparative study of machine learning-based load balancing in high-speed train system
Panitsas et al. Predictive handover strategy in 6g and beyond: A deep and transfer learning approach
Park et al. SFSH: a novel smart factory SDN-layer handoff scheme in 5G-enabled mobile networks
Zhan et al. Aerial video streaming over 3D cellular networks: An environment and channel knowledge map approach
Majid et al. Using an Efficient Technique Based on Dynamic Learning Period for Improving Delay in AI‐Based Handover